Calculating a behavioral path based on a statistical profile

ABSTRACT

A system for directing behavior of a first patient of a plurality of patients towards a behavioral objective includes a patient behavioral path calculator, a patient goal calculator, and a patient monitoring processor. The system also includes an information communication processor and a statistical processor. The patient behavioral path calculator calculates a patient behavioral path based on a statistical profile. The patient goal calculator calculates patient goals along the patient behavioral path toward a behavioral objective. The statistical processor can modify the statistical profile based on a response to a targeted message sent by the information communication processor.

REFERENCE TO RELATED APPLICATIONS

This application is a continuation under 37 C.F.R. §1.53(b) of U.S.patent application Ser. No. 11/604,570 filed Nov. 27, 2006, the entiredisclosure of which is hereby incorporated by reference.

The following co-pending and commonly assigned U.S. patent applicationshave been filed on the same date as the present application: U.S. patentapplication Ser. No. ______, “OPTIMIZING BEHAVIORAL CHANGE BASED ON APATIENT STATISTICAL PROFILE,” (012446-06006BUS), filed herewith; andU.S. patent application Ser. No. ______, “OPTIMIZING BEHAVIORAL CHANGEBASED ON A POPULATION STATISTICAL PROFILE,” (012446-06007BUS), filedherewith, both of which are herein incorporated by reference.

This application relates to and describes further aspects of theembodiments disclosed in the following patent applications, which areincorporated herein in their entirety by reference for all purposes:U.S. patent application Ser. No. 11/604,569, titled “OPTIMIZINGBEHAVIORAL CHANGE BASED ON A PATIENT STATISTICAL PROFILE,” (AttorneyRef. No. 012446-06006AUS), filed Nov. 27, 2006; and U.S. patentapplication Ser. No. 11/604,568, titled “OPTIMIZING BEHAVIORAL CHANGEBASED ON A POPULATION STATISTICAL PROFILE,” (Attorney Ref. No.012446-06007AUS), filed Nov. 27, 2006.

BACKGROUND

Behavior monitoring and altering systems focus on encouraging aparticular patient behavior, whether that behavior is to stop anunhealthy activity, such as smoking, or whether that behavior is toencourage a healthy activity, such as exercising, dieting, adhering to aprescribed medical treatment regimen or maintaining a regular scheduledintake of medication, e.g. insulin. These systems often focus on anindividual and that individual's behavior, resulting in a regimen ofbehavior tailored for that particular person.

However, in the context of chronic disease management, as more and morepeople are recovering outside the purview of human interaction, there isan increased risk that a prescribed regimen will be ignored. As today'slifestyle has become increasingly busier and fast-paced, there remainsvery little time for an individual clinician to ensure that a particularrecommended regimen is followed by his or her patients. Furthermore,there is no guarantee that two people with similar conditions willrespond to a monitoring system, and its accompanying recommendations, inexactly the same way. For example, in the case of two individuals whowish to stop smoking, many individual-specific variables will determinethe likelihood of success that either individual has to actually achievethe goal of stopping smoking, such as their lifestyle or theiravailability to the monitoring system, such as their accessibility to acommunication medium for reporting back to the monitoring system.Additionally, there is no guarantee that either individual will be moresuccessful than the other at stopping a smoking behavior.

Many behavior monitoring and altering systems are established solelyaround a pre-determined behavioral regimen and do not evolve accordingto the individual's needs. Other than through institutional changes,these behavior monitoring and altering systems do not take into accountthat individual's behavior or whether other similarly situatedindividuals have been successful at a particular behavioral change.

Therefore, a need exists for a behavior monitoring and altering systemthat not only evolves according to an individual's behavior andresponses, but also takes into account the likelihood of success of thatindividual achieving his or her desired goal as compared with othersimilarly situated individuals and encourages that individual intoachieving his or her desired goal.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention can be better understood with reference to the followingdrawings and description. The components in the figures are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention. Moreover, in the figures, likereferenced numerals designate corresponding parts throughout thedifferent views.

FIG. 1 is a flowchart of one embodiment of accessing a patientenrollment and monitoring system.

FIG. 2 is a flowchart of one embodiment of enrolling a patient in thepatient monitoring system.

FIG. 3 is a flowchart of one embodiment of receiving and processingpatient enrollment information.

FIG. 4 is a flowchart of one embodiment of associating patientauthentication information with a patient record.

FIG. 5 is a flowchart of one embodiment of selecting and modifying apatient questionnaire.

FIG. 6 is a flowchart of one embodiment of accessing the patientmonitoring system.

FIG. 7 is a flowchart of one embodiment of processing patientstatistical information.

FIG. 8 is a flowchart of one embodiment of creating a patientstatistical profile.

FIG. 9 is a flowchart of one embodiment of modifying a patientstatistical profile.

FIG. 10 is a flowchart of one embodiment of a patient accessing thepatient monitoring system.

FIG. 11 is a flowchart of one embodiment of analyzing a patient responseto a targeted message.

FIG. 12 is a flowchart of one embodiment of modifying a statisticalprofile.

FIG. 13 is a flowchart of one embodiment of activating a failureprevention mechanism.

FIG. 14 is a flowchart of one embodiment of evaluating patient inputusing a statistical processor.

FIG. 15 is a flowchart of one embodiment of the statistical processorperforming a cross-sectional baseline analysis.

FIG. 16 is a flowchart of one embodiment of the statistical processorperforming a longitudinal cohort analysis.

FIG. 17 is a flowchart of one embodiment of the statistical processorperforming a cross-sectional analysis using calculated intervaloutcomes.

FIG. 18 is a graphical illustration of one embodiment of the patientstatistical profiles.

FIG. 19 is a diagram of one embodiment of a behavioral path.

FIG. 20 is a flowchart of one embodiment of contacting a patient whenthe patient fails to contact the patient monitoring system.

FIG. 21 is a block diagram of one embodiment of a patient monitoringsystem.

FIG. 22 is a block diagram of one embodiment of a patient behavioralcalculator.

FIG. 23A is a block diagram of one embodiment of a failure preventionmechanism.

FIG. 23B is a block diagram of another embodiment of the failureprevention mechanism.

FIG. 24 is one example of a patient enrollment report.

FIG. 25 is one example of a patient record.

FIG. 26 is one example showing comments entered into a patient record

FIGS. 27-54 depict examples of individual monthly reports generated byone embodiment of the disclosed patient monitoring system.

DETAILED DESCRIPTION

The patient monitoring system disclosed herein is directed toimplementing methods of statistical process control in helping patientsachieve a desired behavioral objective and/or outcome. In general,statistical process control (“SPC”), is a method for measuring,understanding and controlling variation in a process. SPC has manyaspects, from control charting to process capability studies andimprovement. SPC may be categorized into four basic steps: 1) measuringthe process; 2) eliminating variances within the process to make itconsistent; 3) monitoring the process; and 4) improving the process.This four-step cycle may be employed over and over again for continuousimprovement.

SPC is used in the disclosed patient monitoring system to help patientsachieve a desired behavioral objective and/or outcome by monitoringcurrent patient responses to surveys based on and refining the processused to encourage the current patient and/or other patients to achievethat desired behavioral objective and/or outcome. For example, thepatient monitoring system may use a statistical profile of apatient-population to generate goals, objectives, and fault limits foran individual patient. A patient-population may be a set of patientssimilarly situated based on specified criteria, such as demographics,medical condition(s), symptom(s), medicinal prescriptions, priortreatments currently being administered or previously received, economicdata, or other specified criteria or combinations thereof.

Based on the generated goals, objectives and/or fault limits, thepatient monitoring system prepares one or more targeted messages orsurveys to be delivered to a patient to help the patient achieve thegoals and/or objectives. By monitoring the patient's response to the oneor more targeted messages and/or surveys, the patient monitoring systemrefines the statistical profile of the patient-population tore-calculate the goals, objectives, and fault limits for the patient,other future patients, or a combination thereof. The patient monitoringsystem can further, or alternatively, use the refined or redefinedstatistical profile of the group of patients to help future patientsachieve similar goals and/or objectives. Thus, by using statisticalprocess control, the patient monitoring system can help current and/orfuture patients maximize their ability to achieve a desired goal and/orobjective.

The embodiments herein relate to a system and method for directing andencouraging behavior of a first patient of a plurality of patientstowards a behavioral objective. The system includes a patient behavioralpath calculator, a patient goal calculator, and a patient monitoringprocessor. The system also includes an information communicationprocessor and a statistical processor. The patient behavioral pathcalculator calculates a patient behavioral path based on a statisticalprofile. The patient goal calculator calculates patient goals along thepatient behavioral path toward a behavioral objective. The statisticalprocessor can modify the statistical profile based on a response to atargeted message sent by the information communication processor.

FIG. 21 is a block diagram of a patient monitoring system 2108 accordingto one embodiment. The patient monitoring system 2108 includes aninformation communication interface 2110 coupled with an informationcommunication processor 2112. The information communication interface2110 facilitates communication between a clinician 2102, a patient 2104,an external data source 2106, or combinations thereof, and theinformation communication processor 2112 through a communication network2132. The information communication interface 2110 also facilitatescommunication between the clinician 2102, the patient 2104, the externaldata source 2106, or combinations thereof, and the patient enrollmentprocessor 2114. The information communication interface 2110 furtherfacilitates communication with the patient monitoring processor 2120.Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware and softwarebased components.

To clarify the use in the pending claims and to hereby provide notice tothe public, the phrases “at least one of <A>, <B>, . . . and <N>” or “atleast one of <A>, <B>, . . . <N>, or combinations thereof” are definedby the Applicant in the broadest sense, superceding any other implieddefinitions herebefore or hereinafter unless expressly asserted by theApplicant to the contrary, to mean one or more elements selected fromthe group comprising A, B, . . . and N, that is to say, any combinationof one or more of the elements A, B, . . . or N including any oneelement alone or in combination with one or more of the other elementswhich may also include, in combination, additional elements not listed.

As used herein, the term “processor” means a processor implemented inhardware, software or a combination thereof. For example, a “processor”may be a processor implemented as a reduced instruction set computer(RISC), a processor implemented as a complex instruction set computer(CISC), or combination thereof. In another example, a “processor” may bea software module written in a computer programming language, such asFortran, C, C#, .NET, Java, Javascript, Splus, R, SAS, or combinationsthereof. Other computer programming languages are also possible. Asanother example, a “processor” may be a separate computer system, withits own internal processor (such as an x86-based processor or RISCprocessor), memory (including both RAM and internal storage devices),input devices (such as a keyboard, microphone, and mouse) and outputdevices (such as a visual display device and an audio display device)coupled with the patient monitoring processor 2120 using a networktechnology that is presently known or later developed, such as Ethernet,802.11a/b/g, Bluetooth, or combinations thereof.

Where the clinician 2102 uses the communication network 2132 tocommunicate with the patient monitoring system 2108, the patient 2104 orthe external data source 2106 can use the same communication network2132 to communicate with the patient monitoring system 2108. In analternative embodiment, the patient 2104 and the external data source2106 use alternative communication networks 2132 to communicate with thepatient monitoring system 2108. For example, where the clinician 2102uses a packet-switched communication network 2132, such as the Internet,to communicate with the patient monitoring system 2108, the patient 2104may use a circuit-switched network, such as the telephone network, andthe external data source 2106 may use a combination of acircuit-switched network and a packet-switched network.

In one embodiment, the information communication processor 2112processes communication transmissions sent from and received by thepatient monitoring system 2108 via the information communicationinterface 2110, as will be explained with reference to FIG. 1 below. Theinformation communication processor 2112 is also coupled with anauthorized users database 2134 that stores and maintain records of usersauthorized to access the patient monitoring system 2108. The authorizedusers database 2134 is accessible by the patient enrollment processor2114 or the patient monitoring processor 2120 via the informationcommunication processor 2112.

The patient monitoring system 2108 further includes a patient enrollmentprocessor 2114 coupled with the information communication processor2112, which allows a clinician 2102 to communicate with the patientenrollment processor 2114 for enrolling new patients in the patientmonitoring system 2108. Alternatively, a patient 2104 may communicatewith the patient enrollment processor 2114 such as to self-enroll. Thepatient enrollment processor 2114 is coupled with a patient recorddatabase 2116 which, in one embodiment as will be explained in detailbelow with reference to FIG. 2, stores records of patients enrolled inthe patient monitoring system 2108. The patient enrollment processor2114 is also coupled with a patient questionnaire database 2118. Asexplained with reference to FIG. 5, the patient questionnaire database2118 stores predetermined questionnaires selectable by the clinician2102 for associating with a patient record stored in the patient recorddatabase 2116. The patient enrollment processor 2114 may be configuredto access the patient record storage 2116 and the patient questionnairedatabase 2118 as will be described.

The patient monitoring system 2108 additionally includes a patientmonitoring processor 2120 coupled with the information communicationinterface 2110 via the information communication processor 2112. Thepatient monitoring processor 2120 may communicate with either theclinician 2102, the patient 2104, or the external data source 2106. Aswill be explained with reference to FIG. 6, the clinician 2102communicates with the patient monitoring processor 2120 after enrollinga new patient in the patient monitoring system 2108 to initiallyestablish a patient statistical profile. The clinician 2102 may lateraccess the patient monitoring system 2108 to update the stored patientstatistical profile. As will be discussed, the initial state of thepatient statistical profile may be initially undefined, to be updatedand refined based on interaction with the patient, clinician or othersource, it may be based on a previously developed population statisticalprofile, it may be based on patient specific data obtained by the system2108 via the patient, clinician or other source, or the patientstatistical profile may be initially defined base on a combinationthereof.

In general, a population statistical profile is model of apatient-population, such that for a given input of an individualpatient, the population statistical profile is able to produce apredicted output, e.g. the most likely output from among the modeledpatient-population, based on the given input. In one embodiment, thepopulation statistical profile is continually updated with feedback fromindividual patient experiences using principles of statistical processcontrol. The system 2108 may include multiple population statisticalprofiles associated with various overlapping and/or non-overlappingpatient populations defined, as was described above, based on patientdemographics, medical condition(s), symptom(s), prescribed medications,etc., or combinations thereof. The population statistical profileincludes statistical information which may further help patientsenrolled in the patient monitoring system 2108 to achieve a particularbehavioral goal and/or a behavioral objective. Each patient may havetheir own patient statistical profile generated based on a particularpopulation statistical profile, covering the patient population whichincludes the given patient, and refined based on the individualexperiences of the patient, the population or a combination thereof.Alternatively, each patient may utilize a particular populationstatistical profile, rather than having an individual patientstatistical profile, which is refined based on the experiences of theassociated population, including or excluding the given patient. Thepatient and/or population statistical profile may also includeinformation that allows the patient monitoring system 2108 to determinethe types of behavior modification treatments that are successful inachieving a particular behavioral goal. The statistical profile may alsoinclude information as to what types of treatments to start first beforestarting another treatment. For example, the statistical profile mayinclude success rates based on a percentage of population for aparticular treatment. The statistical profile may also include failurerates based on a percentage of population for a particular treatment.The statistical profile may also provide information as to how aparticular goal should be achieved based on responses to particulartreatments from patients undergoing that treatment, similar to pediatricgrowth curves, which indicate percentiles of typical growth rates. Thestatistical profile may also include reference information, indicatingwhich statistical methods, databases, articles or expert informationwere used to derive the profile and the time stamp of the profile andeach source. Other types of statistical information for achievingbehavior modification are also possible.

As will be explained with reference to FIG. 10, the patient 2104communicates with the patient monitoring processor 2120 to answertargeted messages sent by the patient monitoring processor 2120 based onthe questionnaire(s) previously associated with the patient's 2104stored record and the patient's 2104 stored statistical profile. Theresponse(s) provided by the patient 2104 may be used by the patientmonitoring processor 2120 to modify the stored statistical profileassociated with the patient 2104, may be used by the patient monitoringprocessor 2120 to modify the stored statistical profile associated witha second patient similarly situated as the first patient 2104, may beused to modify the statistical profile(s) associated with a set orpopulation of patients which contains the patient, or combinationsthereof.

According to the embodiment of FIG. 21, the patient monitoring processor2120 is further coupled with a statistical processor 2122, a patientbehavioral calculator 2124, a patient goal analyzer 2126, and a failureprevention mechanism 2128. In one embodiment, the statistical processor2122 generates a statistical profile for the patient 2104 based onstatistical information provided by the clinician 2102, provided by theexternal data source 2106, or combinations thereof. The statisticalprocessor 2122 may also be used to generate a new statistical profile ormodify an existing statistical profile based on responses by the patient2104 to one or more targeted messages sent by the patient monitoringprocessor 2120. The statistical processor 2122 is coupled with thepatient behavioral calculator 2124 and a statistical profile storage2130. The patient goal analyzer 2126 may also be coupled with thestatistical processor 2122.

As will be explained in further detail below, the patient behavioralcalculator 2124 may calculate a behavioral path to a behavioralobjective for the patient 2104 based on a statistical profile calculatedby the statistical processor 2122. The patient behavioral calculator2124 may also calculate a plurality of intermediate goals along thebehavioral path for achieving the behavioral objective. As will beexplained with reference to FIG. 12, in one embodiment, the patientbehavioral calculator 2124 may also be configured to re-calculate thebehavioral path and the plurality of intermediate goals based on whetherthe statistical processor 2122 modified the statistical profileassociated with the patient 2104.

The patient goal analyzer 2126 is coupled with the patient monitoringprocessor 2120 and the statistical processor 2122. The patient goalanalyzer 2126 is operative to calculate or determine whether the patient2104 has achieved, in whole or in part, an intermediate goal along thecalculated behavioral path towards the behavioral objective. Based onthe result determined or calculated by the patient goal analyzer 2126,the patient goal analyzer 2126 may initiate the failure preventionmechanism 2128 to prevent the patient 2104 from failing to achieve thebehavioral objective. As explained with reference to FIG. 13, activatingthe failure prevention mechanism 2128 may include alerting a person,such as the clinician 2102 or the patient 2104, as to the patient's 2104failing progress or may include sending a failure prevention message tothe patient 2104 when the patient 2104 next initiates a session with thepatient monitoring system 2108.

FIG. 22 depicts a block diagram of one embodiment of the patientbehavioral calculator 2124, described above. In one embodiment, thepatient behavioral calculator 2124 is implemented in a processor, asdescribed above. The patient behavioral calculator 2124 includes apatient behavioral path calculator 2202 coupled with a patient goalcalculator 2204 and a patient behavioral recombiner 2206. The patientgoal calculator 2204 is also coupled with the patient behavioralrecombiner 2206. In one embodiment, the patient goal calculator 2204 isa processor. The patient behavioral path calculator 2202 calculates thebehavioral path of the patient based on an initial state of the patientsubmitted by the clinician and a statistical profile associated with thepatient, which, as described above, may have been based on a populationstatistical profile associated with a give patient population thatincludes the patient. The initial state of the patient includesinformation such as the patient's current health, demographicinformation, or other personal information. The initial state of thepatient 2104 may also be the state of the patient 2104 prior to asubsequent communication session between the patient 2104 and thepatient monitoring system 2108.

The patient behavioral path calculator 2202 also communicates with thepatient goal calculator 2204, which allows the patient goal calculator2204 to calculate one or more intermediate patient behavioral goalsalong the patient's behavioral path. For example, the patient goalcalculator 2204 may use the behavioral path to determine where along thebehavioral path the patient should have intermediate behavioral goals.Alternatively, or in addition to using the behavioral path to determinethe patient's intermediate goals, the patient goal calculator 2204 mayalso use the patient statistical profile, the population statisticalprofile, previously calculated goals and/or objectives for otherpatients, or combinations thereof.

The patient goal calculator 2204 communicates the calculatedintermediate behavioral goals to the patient behavioral recombiner 2206.The patient behavioral recombiner 2206 is operable to combine theintermediate behavioral goals outputted by the patient goal calculator2204 and the patient behavioral path outputted by the patient behavioralpath calculator 2202. By combining the patient behavioral path with thecalculated intermediate behavioral goals, the patient behavioralrecombiner 2206 is able to produce a complete behavioral path for thepatient monitoring processor 2120. In one embodiment, the patientbehavioral recombiner 2206 is a processor.

FIG. 23A is a block diagram of one embodiment of a failure preventionmechanism 2128. The failure prevention mechanism 2128 is operative toone or more failure prevention messages. A failure prevention message isa message designed to prevent the patient 2104 from failing to achieve apatient behavioral goal and/or a patient behavioral objective. Thefailure prevention message may be a positive reinforcement message, anegative reinforcement message, or a combination thereof. For example,the failure prevention message may include encouraging words to motivatethe patient to continue along the behavioral path. The failureprevention message may also include disparaging words to motivate thepatient to continue along the behavioral path.

In the embodiment shown in FIG. 23A, the failure prevention mechanism2128 is a human alert system. The failure prevention mechanism 2128includes a failure communication interface 2302 coupled with a failurecommunication processor 2304. The failure communication interface 2302is coupled with a human agent via a telephone 2306, a human agent via acomputer 2308, and a human agent via a personal display assistant (PDA)2310. In one embodiment, the failure communication interface 2302 is awired interface, such as an Ethernet port, a parallel communicationport, a serial communication port, a USB port, a wireless interface,such as an infrared receiver, a radio signal receiver, a Bluetoothreceiver, or other equivalent communication interface, or combinationthereof. The failure communication interface 2302 is operable to receivethe notification from the patient goal analyzer 2126 or the patientmonitoring processor 2120 to activate the human alert system. Thefailure communication interface 2302 communicates with the failurecommunication processor 2304 to send the notification from the patientmonitoring processor 2120 or the patient goal analyzer 2126 to activatethe human alert system.

After the failure communication processor 2304 has received anotification to activate the human alert system, the failurecommunication processor 2304 alerts the human agents coupled with thefailure communication interface 2302. In one embodiment, the failurecommunication processor 2304 sends a message to the human agentsconnected with the failure communication interface 2302 alerting thehuman agents that the patients has failed to meet a behavioral goaland/or a behavioral objective. The human agents coupled with the failurecommunication interface 2302 may include, but are not limited to, theclinician, a health-care provider, a family relative of the patient, orcombination thereof. The message sent from the failure communicationprocessor 2304 may be an audible or visual message depending on how thehuman agent is coupled with the failure communication interface 2302.For example, if the human agent 2306 is coupled with the failurecommunication interface 2302 using a telephone, the message sent fromthe failure communication processor 2304 is an audible message. Inanother example, the human agent 2308 coupled with the failurecommunication interface 2302 using a computer and human agent 2310coupled with the failure communication interface 2302 using a PDAreceive an audible message, a visual message, or a combination thereof.

FIG. 23B is a block diagram of another embodiment of the failureprevention mechanism 2128. In the embodiment shown in FIG. 23B, thefailure prevention mechanism 2128 includes a failure communicationinterface 2302 coupled with the failure communication processor 2304.The failure communication processor 2304 is coupled with the failureprevention database 2312. The failure prevention database 2312 storesfailure prevention messages selectable by the failure communicationprocessor 2304 based on the notification sent by the patient monitoringprocessor 2120 or the patient goal analyzer 2126. As will be discussedwith respect to FIG. 13, the failure communication processor 2304, thepatient monitoring processor 2120, or the patient goal analyzer 2126,are capable of selecting a failure prevention message from the failureprevention database 2312. In one embodiment, the failure preventiondatabase 2312 is a software-implemented database residing in the samecomputer system as the failure communication processor 2304. In anotherembodiment, the failure prevention database 2312 is a series of fileslogically arranged in an operating system, such that each filerepresents an individual patient record. In yet a further embodiment,the failure prevention database 2312 resides on a separate computersystem, wherein the computer system has its own internal processor (suchas an x86-based processor or RISC processor), memory (including both RAMand internal storage devices), input devices (such as a keyboard,microphone, and mouse) and output devices (such as a visual displaydevice and an audio display device), and is coupled with the failurecommunication processor 2304 using a network technology such asEthernet, 802.11a/b/g, Bluetooth, or combinations thereof.

The system 2108 is accessible by various entities, referred to as“actors” for various purposes, referred to as “roles.” For discussionpurposes, the description accompanying FIGS. 1-20 refers to actorsincluding the clinician 2101, patient 2104 and external data source(s)2106 and the particular roles with which they access the system 2108.While the discussion below differentiates between the clinician 2102,the patient 2104, and the external data source 2106 accessing thepatient monitoring system 2108, it should be understood that any one ofthese actors can be substituted for another, i.e. each entity may accessthe system in under the guise of one or more roles, which may overlapwith the roles of other entities. For example, where the descriptionbelow discusses the clinician 2102 accessing the patient monitoringsystem 2108, it should also be understood that the patient 2104 or theexternal data source 2106 may also access the patient monitoring system2108 as the clinician 2102 would. Similarly, where the description belowdiscusses the patient 2104 or the external data source 2106 accessingthe patient monitoring system 2108, it should be understood that theclinician 2102 may also access the patient monitoring system 2108 in asimilar manner, such as where the clinician 2102 is acting on behalf ofthe patient 2104 or the external data source 2106. In one implementationof the monitoring system 2108, the patient 2104 may self-enrollthemselves in the monitoring system 2108, define their own goals andmonitor their own progress. In this implementation, the patient 2104acts in the roles of both a patient 2104 and a clinician 2102.

Furthermore, the actors discussed herein, e.g. the clinician 2102, thepatient 2104, and the external data source 2106, are not limitedthereto. For example, the patient 2104 may authorize a surrogate to acton behalf of the patient 2104. Similarly, the clinician 2102 or theexternal data source 2106 may authorize a third-party to act on behalfof the clinician 2102 or the external data source 2106, such as wherethe clinician 2102 authorizes a health management organization orhospital to act on behalf of the clinician 2102. In these instances, thepatient monitoring system 2108 may further be modified to accept accessattempts and changes to the patient monitoring system 2108 made by thesethird-parties. For example, the authorized users database 2134 may bemodified with rights restrictions so as to distinguish between partieswith access-only (e.g., read-only) authorization, modification (e.g.,write) authorization, and execution (e.g., execute) authorization, orcombinations thereof. As an example, a surrogate of the patient 2104 mayhave access-only authorization, the patient 2104 may have modificationauthorization, and the clinician 2102 may have execution authorization.These rights restrictions would further limit or expand the ability ofthe user (e.g., the clinician 2102, the patient 2104, a surrogate, theexternal data source 2106, etc.) currently accessing the system, suchthat certain tasks may only be performed if the user has an authorizedset of right restrictions. In one embodiment, these right restrictionsare stored and maintained by the authorized users database 2134.

Turning now to FIG. 1 is a flowchart of one embodiment of the operationof accessing a patient enrollment and monitoring system. As shown inFIG. 1, the patient monitoring system 2108 receives a session initiationrequest from a data source (Block 102). The initiation request mayoriginate from a clinician 2102, a patient 2104, and/or an external datasource 2106. While the clinician 2102, the patient 2104, and theexternal data source 2106, are shown in communication with the patientmonitoring system 2108, in an alternative embodiment other entities mayalso be in communication with the patient monitoring system 2108 aswell. For example, a healthcare management organization (not shown) maybe in communication with the patient monitoring system 2108 using anautomated service. In yet another alternative embodiment, more than oneentity is capable of accessing the patient monitoring system 2108 duringa given time interval, either simultaneously, substantiallysimultaneously, sequentially or combinations thereof. For example,clinician 2102, patient 2104, or external data source 2106 could accessthe patient monitoring system 2108 substantially simultaneously.Alternatively, while the clinician 2102 is accessing the patientmonitoring system 2108, the patient monitoring system 2108 may preventthe patient 2104 and the external data source 2106 from accessing thepatient monitoring system 2108.

The external data source 2106 is a device, organization, other entity,or combination thereof, capable of providing patient information to thepatient monitoring system 2108. In one embodiment, the external datasource 2106 is a glucometer used for measuring a patient's glucose leveland programmed to access the patient monitoring system 2106 at scheduledtime intervals. In another embodiment, the external data source 2106 isan electronic scale used for measuring a patient's weight and programmedto access the patient monitoring system 2106 at scheduled timeintervals. The external data source 2106 may also be configured toaccess the patient monitoring system 2108 based on pre-determinedcriteria, such as a patient's glucose level or a patient's weight. Theexternal data source 2106 could also be an entity other than anelectronic or mechanical device, such as a health managementorganization, insurance company, employer, physician, clinician, or anelectronic system, such as a database or other system operated thereby,capable of accessing the patient monitoring system 2108.

When the clinician 2102, the patient 2104, or the external data source2106 sends a session initiation request to the patient monitoring system2108, the patient monitoring system 2108 then prompts the data source,such as the clinician 2102, to provide user identification information(Block 104). The patient monitoring system 2108 prompts the clinician2102 using the information communication processor 2112 via theinformation communication interface 2110. The communication network 2132used to communicate with the patient monitoring system 2108 may affectthe type of information communication interface 2110 used to communicatewith the clinician 2102. For example, the communication network 2132 mayinclude a packet-switched network, a circuit-switched network, or acombination thereof. In one embodiment, the clinician 2102 contacts thepatient monitoring system 2108 using a telephone via the Plain OldTelephone Service (POTS). Where the clinician 1508 uses a telephone tocontact the patient monitoring system 2108, the clinician maycommunicate with the patient monitoring system 2108 through theinformation communication interface 2110 using dual tone multi-frequency(“DTMF”) signaling, TTY device, via voice recognition, or combinationsthereof. The information communication interface 2110 interacts with theclinician 2102 by providing voice prompts to the clinician 2102. Forexample, the information communication interface 2110 may provide avoice menu to the clinician 2102 which presents instructions and/oravailable options. The IVR interface facilitates communication with theclinician via computer generated, or computer provided pre-recorded,audible prompts. Using the IVR, the information communication interface2110 allows the clinician to respond using the touch-tone keys of theclinician's keypad and/or by speaking responses. The informationcommunication interface 2110 may then record, encode, translate and/orconvert the verbal response or key presses and transmit them to theinformation communication processor 2112.

Where the clinician 2102 communicates with the patient monitoring system2108 using a telephone, the information communication interface 2110 mayprompt the clinician 2102 to provide, verbally or via the keypad, apersonal identification number (PIN) for authorizing access to thepatient monitoring system 2108 (Block 104). In an alternativeembodiment, the information communication interface 2110 uses voicerecognition technology to determine whether the clinician 2102 isauthorized to access the patient monitoring system 2108. The informationcommunication interface 2110 then communicates with the informationcommunication processor 2112 to determine whether the clinician 2102 isauthorized to access the patient monitoring system 2108.

In an alternative embodiment, the clinician 2102 uses a telephoneconnected to a packet-switched network to contact the patient monitoringsystem 2108, which is connected to a circuit-switched network. Forexample, the clinician 2102 may contact the patient monitoring system2108 using voice-over-IP (VOIP) technology and a voice-over-IP (VOIP)protocol, such Session Initiation Protocol (“SIP”), an H.323 protocol,other VOIP protocols, or a combination thereof.

In another embodiment the clinician 2102 contacts the patient monitoringsystem 2108 using a packet-switched network, such as where the clinician2102 uses a computer, personal digital assistant, cell phone or othersuitable general purpose or dedicated device to communicate with theinformation communication interface 2110. Where the clinician 2102 usesa computer to contact the patient monitoring system 2108 over apacket-switched network, the clinician 2102 may use a computer coupledwith a wired and/or wireless network, such as private or public network,e.g. the Internet, intranet or combination thereof, to communicatethrough the network with the information communication interface 2110.In an alternative embodiment, the computer is coupled with a modemcapable of using POTS to communicate with the patient monitoring system2108. In this alternative embodiment, the communication network 2132 mayinclude both a circuit-switched network and a packet-switched network.Where the clinician 2102 uses a computer to contact the patientmonitoring system 2108, the computer may use various protocols tocommunicate with the patient monitoring system 2108 through theinformation communication interface 2110. For example, the computer mayuse application layer protocols, such as HTTP, FTP, SMTP, SSH, transportlayer protocols, such as TCP, UDP, RUDP, network protocols, such asICMP, IGMP, ARP, or combinations thereof.

Where the clinician 2102 uses HTTP or other similar protocol tocommunicate with the patient monitoring system 1058, the informationcommunication interface 2110 presents a textual and/or graphicalinterface, such as an Internet web site, for communicating with theclinician 2102. In this alternative embodiment, the clinician 2102 maybe prompted to provide a username and password to the Internet web sitefor accessing the patient monitoring system 2108 (Block 104). Theinformation communication interface 2110 then communicates this usernameand password combination to the information communication processor 2112(Block 106). The information communication processor 2112 thendetermines whether the clinician 2102 is authorized to access thepatient monitoring system 2108 by referring to an authorized userdatabase 2134 (Block 108). In an alternative embodiment, the Internetweb site may request that the clinician 2102 provide a pre-generatedsecurity certificate for accessing the patient monitoring system 2108.The information communication interface 2110 then relays this securitycertificate to the information communication processor 2112, which thencompares the security certificate with the security certificates ofauthorized users stored in the authorized user database 2134. In yetanother embodiment, the Internet web site may request that the clinician2102 provide biometric information to the information communicationinterface 2110, such as a real-time scan of the clinician's fingerprint.The information communication interface 2110 then relays the biometricinformation to the information communication processor 2112, which thencompares the clinician provided biometric information with a database ofbiometric information of authorized users 2134.

In one embodiment, the authorized users database 2134 is asoftware-implemented database residing in the same computer system asthe information communication processor 2112. In another embodiment, theauthorized users database 2134 is a series of files logically arrangedin an operating system, such that each file represents an individualpatient record. The authorized users database 2134 could further resideon a separate computer system, wherein the computer system has its owninternal processor (such as an x86-based processor or RISC processor),memory (including both RAM and internal storage devices), input devices(such as a keyboard, microphone, and mouse) and output devices (such asa visual display device and an audio display device), and is coupledwith the information communication processor 2112 using a networktechnology such as Ethernet, 802.11a/b/g, Bluetooth, or combinationsthereof.

Once the information communication processor 2112 has received the useridentification information from the information communication interface2110, the information communication processor 2112 then determineswhether to allow the clinician 2102 access to the patient monitoringsystem 2108 (Block 108). If the information communication processor 2112determines that the clinician 2102 is not authorized to access thepatient monitoring system 2108, such as where the clinician provideduser identification information does not exist in the authorized usersdatabase 2134, the information communication processor 2112 relays thisfact to the information communication interface 2110, which may thenprompt the clinician 2102 to re-provide the clinician's useridentification information. In an alternative embodiment the informationcommunication interface 2110 may deny access to the clinician 2102 andthen require the clinician 2102 to wait for a predetermined amount oftime before again accessing the patient monitoring system 2108. Forexample, if the information communication processor 2112 determines thatthe clinician 2102 has not provided authorized user identificationinformation to access the patient monitoring system 2108, theinformation communication interface 2110 may state that the clinician2102 must wait two hours before again attempting to access the patientmonitoring system 2108. In yet another alternative embodiment, theinformation communication processor 2112 allows a predetermined numberof access failures before denying access to the clinician. For example,the information communication processor 2112 may allow the clinician2102 to attempt to provide valid user identification information up tofive times before determining that the clinician 2102 is not authorizedto access the patient monitoring system 2108.

Once the information communication processor 2112 has determined thatthe clinician 2102 is authorized to access the patient monitoring system2108, the information communication interface 2110 provides one or moreoptions to the clinician 2102 as to how to proceed (Block 110). Forexample, the information communication interface 2110 may communicate aquestion or menu to the clinician 2102 as to whether the clinician 2102wants to enroll a new patient in the patient monitoring system 2108(Block 114) or whether the clinician 2102 wants to access a previouslystored patient's record (Block 118). If the clinician 2102 has initiatedcommunication with the patient monitoring system 2108 using a telephone,this question or menu is presented to the clinician 2102 using theaforementioned IVR interface. Alternatively, where the clinician 2102has initiated communication with the patient monitoring system 2108using a computer, this question or menu may be presented textually orgraphically via a web page of the Internet web site.

Where the clinician 2102 provides a response that the clinician wants toenroll a new patient in the patient monitoring system 2108 (Block 112),the patient enrollment processor 2114 facilitates the process ofenrolling a new patient (Block 114). As shown in FIG. 21, the clinician2102 communicates with the patient enrollment processor 2114 via theinformation communication interface 2110 coupled with the informationcommunication processor 2112. In one embodiment, the patient enrollmentprocessor 2114 could be the same processor as that of the informationcommunication processor 2112. In another embodiment, the patientenrollment processor 2114 is a distinct processor.

FIG. 2 is a flowchart showing one embodiment of the operation ofenrolling a patient in the patient monitoring system 2108. Once theclinician 2102 has chosen to enroll a new patient in the patientmonitoring system 2108, the patient enrollment processor 2114 receivesthe patient enrollment information via the information communicationinterface 2110 (Block 202). As shown in FIG. 3, receiving the patientenrollment information may first include the clinician 2102 initiatingthe enrollment session (Block 302). Initiating the enrollment sessionmay be based on the clinician's response to the option of whether toenroll a new patient in the patient monitoring system 2108 or to accessthe patient monitoring system 2108. When the clinician 2102 hasinitiated the patient enrollment session, the patient enrollmentprocessor 2114 instructs the information communication interface 2110 toprompt the clinician 2102 to provide patient enrollment information(Block 304). In one example, where the clinician 2102 communicates usinga telephone, the information communication interface 2110 presentprompts to the clinician 2102 using an IVR interface. In anotherexample, the information communication interface 2110 presents anInternet site to the clinician 2102 for providing patient enrollmentinformation. Examples of patient enrollment information include contactinformation for the new patient, such as the patient's telephone number,patient demographic data, and clinical parameters.

Referring briefly back to FIG. 2, after the patient enrollment processor2114 receives the patient enrollment information, the patient enrollmentprocessor 2114 proceeds to process the patient enrollment information(Block 204). As shown in FIG. 3, the patient enrollment processor 2114analyzes the enrollment information on a real-time basis as it isprovided to the patient enrollment processor 2114 (Block 306). Forexample, the patient enrollment processor 2114 might check to determinethat a valid phone number has been provided before prompting theclinician 2102 to provide demographic information (Block 308). In analternative embodiment, the patient enrollment processor 2114 acceptsall of the patient enrollment information before analyzing the receivedpatient enrollment information for its accuracy and/or validity (Block308). If the patient enrollment processor 2114 determines that thepatient enrollment information is not valid, such as receiving a stringof letters instead of a string of numbers for the patient's phonenumber, the patient enrollment processor 2114 instructs the informationcommunication interface 2110 to re-prompt the clinician 2102 to providepatient enrollment information (Block 310). In an alternativeembodiment, the patient enrollment processor 2114 presents to theclinician 2102 an option to review the patient enrollment informationbefore storing the patient enrollment information in the patient recorddatabase 2116.

In one embodiment of the patient monitoring system 2108, the patientenrollment processor 2114 creates a data record for the new patientbased on the patient enrollment information in a patient record database2116 coupled with the patient enrollment processor 2114. It is alsopossible that the patient record database 2116 is communicativelycoupled with the patient enrollment processor 2114 from another system.In an alternative embodiment, the patient enrollment processor 2114 iscoupled with multiple databases and may prompt the clinician to selectone or more databases in which to create the new patient record. Forexample, the clinician 2102 may be authorized to access multipledatabases, such as where the clinician 2102 maintains a database forsmoking patients and another database for overweight patients (Block312). Alternatively, separate databases may be maintained based on otherattributes such as gender, insurance carrier, etc., wherein a patientrecord may be created and maintained one or more of each of the relevantdatabases. In this embodiment, the patient enrollment processor 2114communicates with the information communication interface 2110 toprovide an option to the clinician 2102 to select a particulardatabase(s). Once the clinician 2102 has provided the patient enrollmentinformation requested by the patient enrollment processor 2114 and thepatient enrollment processor 2114 has checked the clinician providedpatient enrollment information, the patient enrollment processor 2114then creates a new patient record in the patient record database 2116(Block 314).

In one embodiment, the patient record database 2116 is asoftware-implemented database residing in the same computer system asthe patient enrollment processor 2114. In another embodiment, thepatient record database 2116 is a series of files logically arranged inan operating system, such that each file represents an individualpatient record. In yet a further embodiment, the patient record database2116 resides on a separate computer system, wherein the computer systemhas its own internal processor (such as an x86-based processor or RISCprocessor), memory (including both RAM and internal storage devices),input devices (such as a keyboard, microphone, and mouse) and outputdevices (such as a visual display device and an audio display device),and is coupled with the patient enrollment processor 2114 using anetwork technology such as Ethernet, 802.11a/b/g, Bluetooth, orcombinations thereof.

Referring back to FIG. 2, once the patient enrollment processor 2114 hascreated the new patient record, the patient enrollment processor 2114then stores the provided patient enrollment information in the createdpatient record (Block 206). In another embodiment, the patientenrollment processor 2114 stores a patient identifier that referencespatient enrollment information stored in an external systemcommunicatively coupled with the patient monitoring system 2108, such asan external electronic medical record system. After the patientenrollment processor 2114 has stored the patient enrollment informationin the new patient record, the patient enrollment processor then promptsthe clinician 2102, via the information communication interface 2110, toselect an authentication mechanism to associate with the created patientrecord for allowing secured access to the newly created patient record(Block 208).

FIG. 4 is an example of associating an authentication mechanism with apatient record. In one embodiment of associating an authenticationmechanism with a patient record, the information communication interface2110 prompts the clinician 2102 to select a patient authenticationmechanism (Block 402). For example, the information communicationinterface 2110 may prompt the clinician 2102 to select between multipleauthentication mechanisms, such as either a patient useridentifier/patient password identification pair or choosing a biometricscheme. If the clinician 2102 is communicating using a telephone, theinformation communication interface 2110 provides this option over thepreviously described IVR. However, if the clinician 2102 iscommunicating with the patient monitoring system 2108 using a computer,the option to choose an authentication mechanism is provided through anInternet web site. Once the clinician 2102 has selected anauthentication mechanism to associate with the patient record, thepatient enrollment processor 2114 then determines which patientauthentication mechanism was chosen (Block 404).

In one example, the clinician 2102 chooses to associate a patient useridentifier/patient password identification pair with the patient record.In this example, the information communication interface 2110 promptsthe clinician 2102 to first provide a patient user identifier (Block406), and then communicates the clinician provided patient useridentifier to the patient enrollment processor 2114. The patientenrollment processor 2114 may then verify the clinician provided patientuser identifier with a list of patient user identifiers retrieved fromthe patient record database 2116 (Block 408). The patient enrollmentprocessor 2114 may also verify the clinician provided patient useridentifier with a list of authorized usernames retrieved from theauthorized users database 2134 via the information communicationprocessor 2112. By comparing the clinician provided patient useridentifier against the patient user identifiers stored in the patientrecord database 2116 or the authorized usernames stored in theauthorized users database 2134, the patent enrollment processor 2114 candetermine whether the clinician 2102 has provided a unique patientidentifier for accessing the patient monitoring system 2108. If thepatient enrollment processor 2114 determines that the clinician providedpatient identifier is not unique, the patient enrollment processor 2114instructs the information communication interface 2110 to prompt theclinician 2102 to re-provide a patient user identifier (Block 406). Ifthe patient enrollment processor 2114 determines that the clinicianprovided patient identifier is unique, the patient enrollment processor2114 instructs the information communication interface 2110 to promptthe clinician 2102 to provide a patient password identificationassociated with the patient user identifier for accessing the patientmonitoring system 2108 (Block 410).

After the clinician 2102 provides a patient password identification ofthe patient user identifier/patient password identification pair, thepatient enrollment processor 2114 compares the patient passwordidentification with a predetermined rule set for complex patientpassword identification (Block 412). For example, the patient enrollmentprocessor 2114 may have a set of rules that specify that: 1) Everypatient password identification must consist of both alphabetic andnumeric characters; and 2) Must be longer than five characters. In thisexample, if the clinician 2102 provides a patient passwordidentification such as “abcde” to the patient enrollment processor 2114via the information communication interface 2110, the patient enrollmentprocessor 2114 will determine that the clinician provided patientpassword identification is unacceptable for the established securityprotocols. To illustrate, and assuming the same set of rules for thesecurity protocol, if the clinician 2102 provides a patient passwordidentification of “12abcd” to the patient enrollment processor 2114 viathe information communication interface 2110, the patient enrollmentprocessor 2114 will determine that the clinician provided useridentifier is acceptable. Once the patient enrollment processor 2114 hasdetermined that the patient user identifier and the patient passwordidentification are acceptable, the patient enrollment processor 2114associates the patient user identifier and patient passwordidentification pair with the patient record (Block 418).

When the patient enrollment processor 2114 finishes associating thepatient authentication mechanism with the patient record, the patientenrollment processor 2114 then instructs the information communicationinterface 2110 to prompt the clinician 2102 to select or provide anadditional patient authentication mechanism (Block 420). If theclinician 2102 chooses to select or provide an additional patientauthentication mechanism, the patient enrollment processor 2114 thenproceeds to communicate to the information communication interface 2110to prompt the clinician to provide or select the desired patientauthentication mechanism (Block 402). However, if the clinician 2102provides a response indicating that the clinician 2102 has decided notto select an additional patient authentication mechanism, the patientenrollment processor 2114 completes the association process (Block 422).For example, the patient enrollment processor 2114 may complete theassociation process by storing the association between the patientauthentication mechanism and the patient record in the patient recorddatabase 2116. The patient enrollment processor 2114 may also store theaccepted patient user identifier and patient password identification inthe authorized users database 2134 via the information communicationprocessor 2112 for future reference. The clinician 2102 may then laterprovide the accepted patient user identifier and patient passwordidentification to a patient 2104 for accessing the patient monitoringsystem 2108.

In an alternative embodiment, the clinician provides an additionalauthentication mechanism for associating with the patient record otherthan, or in addition to, the patient user identifier and patientpassword identification authentication mechanism. In this embodiment,the patient enrollment processor 2114 determines that the clinician 2102wants to associate biometric information with the patient record (Block404). The patient enrollment processor 2114 then instructs theinformation communication interface 2110 to prompt the clinician 2102 toprovide a patient's biometric information for associating with thepatient record (Block 414). The clinician 2102 then provides thebiometric information to the patient enrollment processor 2114 via theinformation communication interface 2110. In one example, the clinicianprovided biometric information may include data representing thefingerprints of the patient associated with the patient record. Inanother example, the clinician provided biometric information mayinclude data representing a voice waveform of the patient associatedwith the patient record. Once the clinician has provided the biometricinformation to the patient enrollment processor 2114 via the informationcommunication interface 2110, the patient enrollment processor 2114 thenanalyzes the clinician provided patient biometric information (Block416).

In analyzing the clinician provided patient biometric information, thepatient enrollment processor 2114 may compare the clinician providedpatient biometric information with pre-existing patient biometricinformation stored in the corresponding patient record. Based on thepre-existing patient biometric information, the patient enrollmentprocessor 2114 can then determine that the clinician 2102 did notprovide patient biometric information corresponding to the patientassociated with the patient record. As an alternative to, or in additionto, the comparison analysis, the patient enrollment processor 2114 mayanalyze the clinician provided patient biometric information todetermine whether the clinician 2102 has provided error-free patientbiometric information. For example, the patient enrollment processor2114 may determine that the clinician provided biometric information isincomplete, such as receiving data indicating four fingerprints ratherthan five fingerprints, or that an error occurred during transmissionusing the communication network 2132, such as in the loss of datarepresenting the patient biometric information.

Once the patient enrollment processor 2114 has determined that theclinician provided patient biometric information is acceptable, thepatient enrollment processor 2114 associates the clinician providedpatient biometric information with the patient record (Block 418).

After the patient enrollment processor 2114 has finished associating theclinician provided patient biometric information with the patientrecord, the patient enrollment processor 2114 communicates to theinformation communication interface 2110 to prompt the clinician 2102 toselect or provide an additional patient authentication mechanism (Block420). If the clinician 2102 chooses to select or provide an additionalpatient authentication mechanism, the patient enrollment processor 2114then instructs the information communication interface 2110 to promptthe clinician 2102 to provide or select the desired patientauthentication mechanism (Block 402). However, if the clinician 2102provides a response indicating that the clinician 2102 has decided notto select an additional patient authentication mechanism, the patientenrollment processor 2114 completes the association process (Block 422).For example, this may involve storing the association between thepatient authentication mechanism and the patient record in the patientrecord database 2116. The patient enrollment processor 2114 may alsostore the accepted clinician provided patient biometric information inthe authorized users database 2134 via the information communicationprocessor 2112 for future reference. The clinician 2102 may then laterprovide or describe the patient biometric information to a patient 2104for accessing the patient monitoring system 2108.

In another embodiment, the patient enrollment processor 2114 allows theclinician 2102 to supplement or replace the current authenticationmechanism associated with a patient record with a later authenticationmechanism. For example, the clinician 2102 may decide to later replacethe patient user identifier/patient password identificationauthentication mechanism with the clinician provided biometricauthentication mechanism, such as with data representing the associatedpatient's fingerprints.

Referring back to FIG. 2, after the clinician 2102 has associated anauthentication mechanism with a patient record, the patient enrollmentprocessor 2114 then proceeds to allow the clinician 2102 to select oneor more questionnaires from the patient questionnaire database 2118 forthe patient associated with the created patient record (Block 210). Inone embodiment, the patient questionnaires include several pre-definedquestionnaires for specific chronic diseases, such as congestive heartfailure, diabetes, asthma or anticoagulation monitoring. Each of thequestionnaires may be generated in advance of a given patient sessionand may be designed to collect specific clinical information from thepatient. Each of the questionnaires may further include one or morequestions. The questionnaires may include a pre-defined static script ofone or more questions designed to elicit particular response from thepatient with respect to a particular chronic disease that the clinicianis trying to manage, or directed to other subject matter such as thecollection of biographical data. For example, all of the questions fromthe script may be presented to the patient in a linear fashion. Inanother example, these scripts include simple branching logic allowingthe patient monitoring system 2108 to select and present one or moresubsequent questions from the pre-defined script based upon the answerto a prior question from the pre-defined script received during thepatient session.

As explained below in reference to FIG. 5, once the clinician 2102 hasselected one or more questionnaires for the patient record, the patientenrollment processor 2114 then communicates to the informationcommunication 2110 to prompt the clinician 2102 whether the clinician2102 wants to modify the selected one or more questionnaires (Block212), such as by adding questions, deleting questions and/or modifyingquestions. If the clinician elects to modify the selected one or morequestionnaires, the patient enrollment processor proceeds to modify thepatient questionnaire (Block 214) as directed by the clinician 2102.Alternatively, the patient enrollment processor 2114 may directlyproceed to associating the selected one or more questionnaires if theclinician 2102 chooses not to modify the selected one or morequestionnaires (Block 216). After the clinician 2102 has finishedmodifying the selected questionnaire, the patient enrollment processor2114 then associates the selected questionnaires with the patient record(Block 216). For example, the patient enrollment processor 2114 maystore the patient questionnaires as part of the patient record stored inthe patient record database 2116. However, the patient enrollmentprocessor 2114 could also create a new record in the patientquestionnaire database 2118 representing the selected one or morequestionnaires and their (or its) association with the patient recordstored in the patient record database 2116.

In one embodiment, the patient questionnaire database 2118 is asoftware-implemented database residing in the same computer system asthe information communication processor 2112. In another embodiment, thepatient questionnaire database 2118 is a series of files logicallyarranged in an operating system, such that each file represents anindividual patient record. In yet a further embodiment, the patientquestionnaire database 2118 resides on a separate computer system,wherein the computer system has its own internal processor (such as anx86-based processor or RISC processor), memory (including both RAM andinternal storage devices), input devices (such as a keyboard,microphone, and mouse) and output devices (such as a visual displaydevice and an audio display device), and is coupled with the patientenrollment processor 2114 using a network technology such as Ethernet,802.11a/b/g, Bluetooth, or combinations thereof.

FIG. 5 illustrates one example of selecting and modifying a patientquestionnaire. After the patient enrollment processor 2114 finishescreating a patient record and associating an authentication mechanismwith the patient record, the patient enrollment processor 2114 generatesa list of all available questionnaires (Block 502). The patientenrollment processor 2114 may generate the list of all availablequestionnaires by accessing the patient questionnaire database 2118. Forexample, each record in the patient questionnaire database 2118 mayrepresent an individual questionnaire and the patient enrollmentprocessor 2114 may access each record to generate a list of allavailable questionnaires. Alternatively, one record in the patientquestionnaire database 2118 may represent all the availablequestionnaires and the patient enrollment processor 2116 could generatethe list of all available questionnaires by accessing the patientquestionnaire database 2118 and retrieving that one record.

After the patient enrollment processor 2114 generates the list of allavailable questionnaires, the patient enrollment processor 2114 thenprovides the questionnaire list to the clinician 2102 via theinformation communication interface 2110 (Block 504). Providing thequestionnaire list to the clinician 2102 may include audibly recitingeach available questionnaire to the clinician 2102, visually displayingeach available questionnaire to the clinician 2102, or combinationsthereof. For example, if the clinician 2102 accessed the patientmonitoring system 2108 using a telephone, the clinician 2102 would beprovided with an audible recording that recites each availablequestionnaire based on the list of questionnaires generated by thepatient enrollment processor 2114. In another example, if the clinician2102 accessed the patient monitoring system 2108 using a computer, theclinician 2102 would be provided with an Internet web site that listseach available questionnaire based on the list of questionnairesgenerated by the patient enrollment processor 2114. An optionrepresenting each available questionnaire may be presented to theclinician 2102 simultaneously or the clinician 2102 might have to revieweach option individually before proceeding to the next option.

Once the patent enrollment processor 2114 provides the list ofquestionnaires to the clinician 2102, the patient enrollment processor2114 then instructs the information communication interface 2110 toprompt the clinician 2102 to choose a questionnaire (Block 506). Theinformation communication interface 2110 then receives the clinician's2102 choice of the selected questionnaire (Block 508). After receivingthe clinician's choice of selected questionnaire, the patient enrollmentprocessor 2114 then instructs the information communication interface2110 to prompt the clinician 2102 whether the clinician 2102 wants tomodify the selected questionnaire (Block 212).

Where the clinician 2102 elects to modify the selected questionnaire,the patient enrollment processor 2114 then instructs the informationcommunication interface 2110 to prompt the clinician 2102 to select atype of modifying action to perform on the selected questionnaire (Block510). Modifying actions include deleting or replacing a particularquestion on the selected questionnaire or altering a particular questionon the selected questionnaire. Modifying actions may also include atailoring process to tailor a selected questionnaire for the patientassociated with the patient record.

Once the clinician 2102 has chosen the modifying action to perform onthe selected questionnaire, the clinician 2102 provides that response tothe patient enrollment processor 2114 via the information communicationinterface 2110. When the patient enrollment processor 2114 receives theclinician's choice of modifying action, the patient enrollment processor2114 then modifies the selected questionnaire according to thatmodifying action. (Block 512). After the patient enrollment processor2114 has modified the selected questionnaire according to the clinicianselected modifying action, the patient enrollment processor 2114 mayinstruct the information communication interface 2110 to prompt theclinician 2102 whether the clinician 2102 wants to select an additionalmodifying action or wants to associate the selected questionnaire asmodified, with the patient record. If the clinician 2102 provides aresponse indicating that the clinician 2102 wants to further modify theselected questionnaire, the patient enrollment processor 2114 mayre-present a list of possible modifying actions and prompt the clinician2102 to select a modifying action via the information communicationinterface 2110 (Block 510). However, the clinician 2102 could alsoprovide a response indicating that the clinician 2102 is satisfied withthe questionnaire and wants to associate the selected questionnaire withthe patient record.

If the clinician 2102 provides a response indicating that the clinician2102 wants to associate the selected questionnaire with the patientrecord, the patient enrollment processor 2114 associates the selectedquestionnaire with the patient record (Block 216). For example, thepatient enrollment processor 2114 may store the patient questionnaire,or a pointer thereto, as part of the patient record stored in thepatient record database 2116. Alternatively, the patient enrollmentprocessor 2114 may create a new record in the patient questionnairedatabase 2118 representing the selected questionnaire and itsassociation with the patient record stored in the patient recorddatabase 2116.

After the patient enrollment processor 2114 associates the selectedquestionnaire with the patient record, the patient enrollment processor2114 then instructs the information communication interface 2110 toprompt the clinician 2102 as to whether the clinician 2102 wants toassociate additional questionnaires with the patient record (Block 514).Where the clinician 2102 provides a response indicating that theclinician 2102 wants to select additional questionnaires, the patientenrollment processor 2114 then provides a list of availablequestionnaires to the clinician 2102 (Block 504). Where the clinician2102 provides a response indicating that the clinician 2102 does notwant to select additional questionnaires, the patient enrollmentprocessor 2114 completes the questionnaire association (Block 516). Asan example of completing the questionnaire association, the patientenrollment processor 2114 may proceed through a verification process toensure that the clinician 2102 does not want to further associatequestionnaires with the patient record. In another embodiment, thepatient enrollment processor 2114 reviews the selected questionnairesand their modifications (if any) with the clinician 2102 beforeproceeding further. Completing the questionnaire association could alsoinclude another verification process to ensure that the modifyingactions performed on the selected questionnaires were correct andaccurate or confirming that the clinician 2102 does not want to furthermodify the selected questionnaires.

Referring back to FIG. 2, after associating the selected one or morequestionnaires with the patient record, the patient enrollment processor2114 completes the enrollment process (Block 218). In completing theenrollment process, the patient enrollment processor 2114 maycommunicate with the clinician 2102 via the information communicationinterface 2110 to review any one of the proceeding actions. For example,the patient enrollment processor 2114 could give the clinician 2102 theopportunity to review the accuracy of the provided patient enrollmentinformation. The patient enrollment processor 2114 could also give theclinician 2102 the opportunity to review, or change, the associatedauthentication mechanism with the patient record, or allow the clinician2102 to replace, or supplement, the associated authentication mechanismwith another or similar authentication mechanism. The patient enrollmentprocessor 2114 could further allow the clinician 2102 to review theselected questionnaires and select additional questionnaires forassociating with the patient record. The patient enrollment processor2114 could additionally allow the clinician 2102 to return to any pointin the enrollment process by providing such option to the clinician 2102via the information communication interface 2110. For example, theinformation communication interface 2110 could provide a list of pointsin the enrollment process to the clinician 2102 as an audible menu,visual list, or a combination thereof.

Referring to FIG. 1, where the clinician 2102 provides a response thatthe clinician 2102 is finished with the enrollment process, the patientenrollment processor 2114 then instructs the information communicationinterface 2110 to prompt the clinician 2102 whether the clinician 2102wants to enroll another patient in the patient monitoring system 2108(Block 116). Where the clinician 2102 provides a response indicatingthat the clinician 2102 wants to enroll another patient, the patientenrollment processor 2114 proceeds to re-start the enrollment process(Block 114). Where the clinician 2102 provides a response indicatingthat the clinician is finished enrolling patients in the patientmonitoring system 2108, the patient enrollment processor 2114 finishesthe clinician session with the clinician 2102 (Block 122). In finishingthe clinician session with the clinician 2102, the patient enrollmentprocessor 2114 may review all of the enrollment actions the clinician2102 has taken during the immediate session. The patient enrollmentprocessor 2114 could also provide an option for the clinician 2102 toreview all of the previous enrollment sessions (if any), and the actionstaken during those previous enrollment sessions (if any). The patientenrollment processor 2114 could also verify the actions taken by theclinician 2102 during the immediate clinician session and whether theclinician 2102 wants to modify any (or all) of the actions taken duringthe immediate clinician session. Once the clinician 2102 indicates thatthe clinician 2102 is satisfied with the enrollment process for the oneor more patients, the patient enrollment processor 2114 terminates thesession between the clinician 2102 and the patient monitoring system2108.

After enrolling one or more patients in the patient monitoring system2108, the clinician 2102 may request to view reports of the enrolledpatients. The clinician 2102 may also view reports of the enrolledpatients in a later session between the clinician 2102 and the patientmonitoring system 2108. FIG. 24 shows one example of a patientenrollment report.

Instead of providing a response indicating that the clinician wants toenroll a new patient, the clinician could provide a response that theclinician wants to access the patient monitoring system (Block 118).Referring to FIG. 6, where the clinician 2102 provides a response thatthe clinician 2102 wants to access the patient monitoring system, thepatient monitoring processor 2120 then communicates with the informationcommunication interface 2110 via the information communication processor2112 to prompt the clinician 2102 to provide patient identificationinformation (Block 602), as was specified in the enrollment process(described above). The patient identification information may be apersonal identification number, biometric information, demographicinformation, a patient user identifier and patient passwordidentification, or combinations thereof.

Once the patient monitoring processor 2120 has received the patientidentification information, the patient monitoring processor 2120 thendetermines whether the patient associated with the patientidentification information has a patient record with the patientmonitoring system 2108. For example, the patient monitoring processor2120 may communicate with the patient record database 2116 to determinewhether the patient associated with the patient identificationinformation has a patient record stored in the patient record database2116. e.g. retrieve any records associated with the patientidentification information.

If the patient monitoring processor 2120 determines that a patientrecord for the patient associated with the patient identificationinformation does not exist in the patient record database 2116, thepatient monitoring processor 2120 may communicate an error to theclinician 2102 that the patient record does not exist for thatparticular patient, or the patient monitoring processor 2120 mayre-prompt the clinician to provide the patient identificationinformation (Block 608). Where the patient monitoring processor 2120determines that the patient associated with the patient identificationinformation has a patient record in the patient record database 2116,the patient monitoring processor 2120 then requests access to orretrieves that patient record (Block 610). Retrieving the patient recordmay include the patient record database 2116 providing a copy of thepatient record, authorizing the patient monitoring processor 2120 toaccess the patient record, or it may include the patient record database2116 creating a temporary patient record locally accessible by thepatient monitoring processor 2120. Other types of retrieval may also bepossible, such as creating a duplicate copy of the patient record forthe patient monitoring processor 2120. The patient monitoring processor2120 may further inform the clinician 2102 that the patient associatedwith the patient identification information has a patient record withthe patient monitoring system 2108.

After the patient monitoring processor 2120 has determined that apatient record exists for the patient associated with the patientidentification information and the patient monitoring processor 2120 hasretrieved the patient record, the patient monitoring processor 2120 thenprocesses patient statistical information (Block 612), explained below.

The patient statistical information, which may be provided by theclinician 2102, or alternatively, by the external data source 2106, mayinclude empirical data, metrics, probabilities and/or statisticsregarding the patient 2104 and/or a population which may include thepatient 2104. For example, the patient statistical information mayinclude personal identifiers, information for linking to otherinformation systems, demographics, occupational history and exposures,educational history, sports and exercise history, diagnostic images andtheir associated interpretations, personal and family health history,current and past medications, current and past behavioral interventionsand the patient's experiences with those treatments, current and pasttest results, allergies, psychological profile and complianceinformation, electronic medical records of varying format, orcombinations thereof. The patient statistical information may alsoinclude information on past and current diagnoses and probablediagnoses, possible treatments and behaviors to modify, how others haveresponded to those treatments and modifications, and the personalcharacteristics of those patients.

FIG. 7 is a flowchart showing the operations of processing patientstatistical information according to one embodiment. Where the patientmonitoring processor 2120 determines that a patient statistical profiledoes not exist for the patient associated with the retrieved patientrecord, the patient monitoring processor 2120 then prompts the clinician2102 to provide patient statistical information for the patient (Block702). Alternatively, at least a portion of the patient statisticalinformation may be derived from the appropriate population statisticalprofile. In an alternative example, the patient monitoring processor2120 prompts an external data source 2106, such as hospital or otherorganization, to provide the patient statistical information. In afurther example, the external data source could be an automated computerprogram or other medical device, such as a glucometer, thermometer,etc., in communication with the patient monitoring processor 2120. Inyet a further embodiment, the external data source could provide patientstatistical information to the patient monitoring processor 2120 atscheduled intervals, random intervals, after completing one or morespecified tasks, such as taking a blood sample, or combinations thereof.

After the patient monitoring processor 2120 prompts the clinician 2102,or alternatively, the external data source 2106, to provide the patientstatistical information, the patient monitoring processor 2120 thenreceives the patient statistical information, defined below (Block 704).

In another embodiment, where the patient statistical profile does notexist for a patient record, an external data source 2106 initiatescommunications with the patient monitoring system 2108 to providepatient statistical information or the patient statistical profile. Forexample, the external data source 2106 could be a separate hospital orother institution that maintains a database of patient statisticalinformation and may provide the patient statistical information to thepatient monitoring system 2108. The hospital or other institution couldprovide the patient statistical information on a predetermined basis, ona dynamic basis, such as where updated or new patient statisticalinformation is provided to the hospital or other institution, orcombinations thereof. In another example, the external data source 2106could be an automated computer program or medical device incommunication with the patient monitoring system 2108 and may providethe patient statistical information to the patient monitoring system2108 on a predetermined basis, a dynamic basis, or combination thereof.

Where the clinician 2102 communicates with the patient monitoringprocessor 2120 using the IVR interface, the IVR interface may presentaudible options to the clinician 2120 for the clinician 2120 to selectin providing the patient statistical information to the patientmonitoring processor 2120. For example, the clinician 2120 could use thekeypad of the telephone in communicating with the IVR interface toprovide choices as patient statistical information to the patientmonitoring processor 2120. In the alternative, the clinician 2120 couldprovide audible responses to the audible options of the IVR interface aspatient statistical information. The patient monitoring processor 2120could then analyze the received audible responses to generate thepatient statistical information for the patient record.

In providing the patient statistical information to the patientmonitoring processor 2120, the clinician 2102 could also use a computerto provide that information. In one embodiment, the clinician 2102communicates with the patient monitoring processor 2120 using anInternet web site as an interface, and the clinician 2102 provides thepatient statistical information to the patient monitoring processor 2120using that Internet web site. For example, the Internet web site mayallow the clinician 2102 to select and submit various pre-definedparameters/options, such as from a bulleted list, drop-down menu, orother input-related field, to the patient monitoring processor 2120,which can use those submitted options directly as the patientstatistical information or can use those submitted options to generatethe patient statistical information. In another alternative, theInternet web site may allow the clinician 2102 to send the patientstatistical information in a file format, such as a Microsoft® Excel®spreadsheet, that is recognizable by the patient monitoring processor2120.

As previously discussed above, one or more actor may provide some or allof the patient statistical information, and the one or more actor maytake on one or more role in providing this patient statisticalinformation. For example, while the patient 2104 is an “actor” that canaccess the patient monitoring system 2108, the patient 2104 can also actwithin the “role” as a clinician 2102 or external data source 2106.Similarly, the external data source 2106 or the clinician 2102 may actwithin the role of the patient 2104. Other combinations of the “actors”clinician 2102, the patient 2104, and the external data source 2106acting within the “roles” of clinician 2102, the patient 2104, and theexternal data source 2106 are also possible. Hence, the provided patientstatistical information may be provided by the clinician 2102, thepatient 2104, or the external data source 2106, or a combinationthereof, acting within the “role” of the clinician 2102, the patient2104, or the external data source 2106. Similarly, other actors notexplicitly shown, such as a surrogate authorized by the patient or theclinician, or a health management organization authorized by the patientor clinician, may take on the “role” of the clinician 2102, the patient2104, the external data source 2106, or combination thereof. Hence,third-parties may also provide the patient statistical informationacting within the “role” of the clinician 2102, the patient 2104, theexternal data source 2106, or combinations thereof.

After the patient monitoring processor 2120 has received the patientstatistical information, the patient monitoring processor 2120 thenanalyzes the patient statistical information (Block 706). The patientmonitoring processor 2120 may be pre-configured to analyze the patientstatistical information for specific anomalies, or the patientmonitoring processor 2120 may be configured to determine the accuracyand/or validity of the received patient statistical information. Forexample, the patient monitoring processor 2120 may be configured with arule set that determines how to analyze the patient statisticalinformation, and the patient statistical information may conform to therules of the rule set. In one embodiment, the rule set may specify thatthe patient statistical information must contain at least the patientgender and age.

In another embodiment, the rule set may specify that the patientstatistical information cannot contain information that would identifythe patient associated with the patient statistical information, such asthe patient's name or patient's Social Security number. The patientmonitoring processor 2120 may analyze the patient statisticalinformation as it is provided in real-time or, alternatively, thepatient monitoring processor 2120 could analyze the patient statisticalinformation after it has been received in its entirety by the patientmonitoring processor 2120. In another embodiment the patient monitoringprocessor 2120 may solicit information on the patient or relatedpossible treatments by a human- or machine-based search methodology,which provides updated information as it is discovered. In thisembodiment, updates to the analyses would be triggered by themodification or addition of information to the patient statisticalinformation. In yet an alternative embodiment, the information providedto the patient monitoring processor 2120 is provided a real-time basis,such that the patient monitoring processor 2120 receives the informationduring a procedure, treatment, or other similar tasks. In anotherembodiment, the information provided to the patient monitoring system2120 is provided on a batch basis, such that the patient monitoringprocessor 2120 receives information based on a group of procedures,treatment, other similar tasks, performed. In this embodiment, the batchinformation provided to the patient monitoring processor 2120 may besent based on a predetermined number of procedures, treatments, or othersimilar tasks performed, or may be sent after a predetermined amount oftime, such as months, weeks, days, other measurements of time, orcombinations thereof, has elapsed.

As the patient monitoring processor 2120 is analyzing the providedpatient statistical information, the patient monitoring processor 2120determines whether to retain the patient statistical information beinganalyzed (Block 708). For example, the patient monitoring processor 2120may analyze the patient's name as part of the provided patientstatistical information, such as to ensure the name is spelled correctlyor corresponds to a patient record. The patient monitoring processor2120 may be configured to reject any patient's name provided with thepatient statistical information. If the patient monitoring processor2120 is configured to reject this type of information, the patientmonitoring processor 2120 will then discard or disregard thatinformation (Block 710). The patient monitoring processor 2120 thenproceeds to analyze the next part or portion of the patient statisticalinformation.

Alternatively, the patient monitoring processor 2120 may be configuredto retain certain types of patient statistical information. For example,the patient monitoring processor 2120 may be configured to retain thetype of behavior submitted with the patient statistical information. Ifthe patient monitoring processor 2120 is configured to retain thisinformation, the patient monitoring processor 2120 then proceeds to thenext part or portion of the statistical patient information. In anotherembodiment, the patient monitoring processor 2120 analyzes all of theprovided patient statistical information in one iteration and retainsonly that information that the patient monitoring processor 2120 isconfigured to retain. Once the patient monitoring processor 2120 hasfinished analyzing all of the information of the patient statisticalinformation, the patient monitoring processor then proceeds to store thepatient statistical information (Block 712).

In storing the patient statistical information, the patient monitoringprocessor 2120 may store the patient statistical information in thepatient record database 2116. For example, the patient monitoringprocessor 2120 may modify the patient record associated with the patientidentification information provided by the clinician 2102 to store thepatient statistical information. Alternatively, the patient monitoringprocessor 2120 creates a new record in the patient record database 2116for storing the patient statistical information. In yet another example,the patient monitoring processor 2120 stores the patient statisticalinformation in the statistical profile database 2130 and associates thatpatient statistical information with the patient record in the patientrecord database 2116. In a further example, the patient monitoringprocessor 2120 creates a temporary storage location, such as in localmemory coupled with the patient monitoring processor 2120, to store thepatient statistical information.

Once the patient monitoring processor 2120 has stored the patientstatistical information, the patient monitoring processor 2120 thenformats the patient statistical information for the patient statisticalprocessor 2122 (Block 714). Formatting the patient statisticalinformation for the patient statistical processor 2122 may also occurbefore the patient monitoring processor 2120 has stored the patientstatistical information. Formatting the patient statistical informationfor the statistical processor 2122 may require that the patientstatistical information is arranged according to a specificationassociated with the statistical processor 2122, such as arranging thestored patient statistical information as comma-delimited text file.Formatting the patient statistical information for the statisticalprocessor 2122 may also involve converting the stored patientstatistical information from one computer-file format to anothercomputer-file format, such as converting a standard text (TXT) file toan Extensible Markup Language (XML) file, Hypertext Markup Language(HTML) file, Microsoft® Excel® (XLS) file, MacBinary (BIN) file or othercomputer-readable file. After the patient statistical information isformatted for the statistical processor 2122, the patient monitoringprocessor 2120 sends the patient statistical information to thestatistical processor 2122 (Block 716).

Referring back to FIG. 6, after processing the patient statisticalinformation (Block 612), the patient monitoring processor 2120 thendetermines whether a patient statistical profile exists for or isassociated with the patient record (Block 614). If the patientmonitoring processor 2120 determines that a patient statistical profileis not associated with the patient record, the patient monitoringprocessor 2120 then proceeds to process patient statistical informationfrom the clinician (Block 612) to create a new patient statisticalprofile (Block 616). FIG. 8 is a flowchart depicting the operation ofcreating a patient statistical profile according to one embodiment.

As shown in FIG. 8, the statistical processor 2122 receives the patientstatistical information from the patient monitoring processor 2120(Block 802). The statistical processor 2122 then analyzes the patientstatistical information (Block 804). Analyzing the patient statisticalinformation may include checking the patient statistical information forerrors, assigning values to variables of the statistical profile,transforming or translating one or more parts of the patient statisticalinformation or ensuring that the patient statistical information is in aformat understood by the statistical processor 2122. In one embodiment,the statistical processor 2122 sends an error to the patient monitoringprocessor 2120 to indicate an error in the statistical information, suchas not being in the correct format or not having enough statisticalinformation to generate a statistical profile. In another embodiment thestatistical processor 2122 sends an acknowledgment to the patientmonitoring processor 2120 indicating that the statistical processor 2122can generate a statistical profile based on the provided statisticalinformation.

After analyzing the statistical information, the statistical processor2122 then generates a new statistical profile for the patient (Block806). Generating a new statistical profile may include processing thestatistical information to obtain a statistical profile that matches thepatient. For example, the statistical processor 2122 could analyze thepatient record from the patient record database 2116 and compare theinformation in the patient record with the received statisticalinformation. In one embodiment, the statistical processor 2122 generatesa statistical profile based on a comparison of the patient informationwith the statistical information. In another embodiment, the statisticalprocessor 2122 analyzes previously stored statistical profiles 2130 todetermine whether a new statistical profile is needed. For example, thestatistical processor 2122 may determine that a new statistical profilebased on the provided statistical information is not needed whencompared with the pre-existing statistical profiles. In yet a furtherembodiment, the statistical processor 2122 refers to a populationstatistical profile stored in the statistical profiles 2130 to generatethe patient statistical profile. For example, the statistical processor2122 may use the population statistical profile as the patientstatistical profile. In another example, the statistical processor 2122may use the provided patient statistical information in conjunction withthe population statistical profile to generate the patient statisticalprofile. In yet another embodiment, the statistical processor 2122generates an empty patient statistical profile without referring toeither the provided patient statistical information or the storedstatistical profiles 2130.

After the statistical processor 2122 has generated a patient statisticalprofile (Block 806), the statistical processor 2122 then associates thepatient statistical profile with the patient's record based on thepreviously provided a patient identification information (Block 808). Inone embodiment, the statistical processor 2122 creates a logicalrelationship between the patient record in the patient record database2116 and a stored statistical profile 2130, such as either a patientstatistical profile or a population statistical profile. In anotherembodiment, the statistical processor 2122 modifies the patient recordstored in the patient record database 2116 to incorporate thestatistical profile. In yet a further embodiment, the statisticalprocessor 2122 modifies a statistical profile to reflect the associationbetween the modified statistical profile and the patient record storedin the patient record database 2116.

Once the statistical processor 2122 finishes associating the patientstatistical profile with the patient record (Block 808), the statisticalprocessor 2122 proceeds to communicate with the patient behavioralcalculator 2124 to calculate a patient behavioral path, described inmore detail below, for the associated patient statistical profile (Block810). In one embodiment, the patient behavioral calculator 2124 issoftware residing on a storage device coupled with the patientmonitoring processor 2120 in the statistical processor 2122.

The patient behavioral path calculated by the patient's behavioralcalculator 2124 is a measure or scale used by the patient monitoringsystem 2108 to determine/gauge the progress of the patient in reaching apatient behavioral goal and/or objective. There may zero, one, or morethan one patient behavioral goals in achieving a behavioral objective. Abehavioral goal may also be a behavioral objective. For example, thepatient behavioral path may include a schedule for the patient toreceive a particular treatment or to perform a particular task. Thepatient's behavioral path may initially include information based oneither the patient statistical profile, a population statisticalprofile, or combinations thereof, such as the frequency to administertreatments or the types of treatments to administer. The patientbehavioral calculator 2124 may calculate the patient behavioral pathbased on the associated patient statistical profile, a populationstatistical profile, the provided patient statistical information, thepatient information from the patient record database 2116, or acombination thereof. For example, the patient behavioral calculator 2124may communicate with the statistical processor 2122 and the patientmonitoring processor 2120 to calculate a new patient behavioral path. Inanother example, the patient behavior calculator 2124 retrieves thestatistical profile associated with the patient record to calculate anew patient behavioral path.

After calculating the patient behavioral path (Block 810), the patientbehavioral calculator 2124 then associates the calculated behavioralpath with the patient record based on the clinician provided patientidentification information (Block 812). In one embodiment, the patientbehavioral calculator 2124 modifies the associated statistical profileto incorporate the calculated patient behavioral path. In anotherembodiment, the behavioral calculator 2124 modifies a patientstatistical profile, a population statistical profile, or combinationthereof, to reflect the association between the modified statisticalprofile and the patient record stored in the patient record database2116. In yet another embodiment, the behavioral calculator 2124 storesthe patient behavioral path in the patient record database 2116.Alternatively, the behavioral calculator 2124 could store the patientbehavioral path in the statistical profiles 2130, another storagemedium, or combinations thereof. Examples of storage mediums includehard drives, flash drives, tape drives, random access memory, EEPROMs,optical media (CD+/−R, DVD+/−R, Blu-ray, HD-DVD, etc.), or combinationsthereof.

After the patient behavioral calculator 2124 associates a patientbehavioral path with the patient record (Block 812), the patientbehavioral calculator 2124, where applicable, may optionally define oneor more intermediate patient behavioral goals along the patientbehavioral path to achieve the patient behavioral objective (Block 814).In one embodiment, the intermediate patient behavioral goals are asequential series of goals, each of which may be achieved beforeproceeding to the next subsequent goal. The patient intermediatebehavioral goals may further be based on, or alternatively, independentof, the one or more statistical profiles associated with the patientrecord. Each of the intermediate patient behavioral goals may be definedalong the patient behavioral path, may lay outside the patientbehavioral path, or a combination thereof. For example, a patient may berequired to achieve one goal, such as to stop smoking five cigarettesfor a day, before proceeding to the next goal, such as stop smokingcigarettes completely for the entire day. In one embodiment, theintermediate patient behavioral goals are calculated to assist thepatient in achieving the patient behavioral objective. In anotherembodiment, the patient's intermediate behavioral goals are calculatedindependently, such that each intermediate behavioral goal is based onachieving the previous intermediate behavioral goal. The patientbehavior calculator 2124 may define a patient behavioral goal as thepatient behavioral objective, as an intermediate patient behavioralgoal, or as a combination thereof.

After the patient behavioral calculator 2124 has defined the one or morepatient behavioral goals (Block 814), the patient behavioral calculator2124 then associates the one or more patient behavioral goals with thepatient record (Block 816). In one embodiment, the patient behavioralcalculator 2124 modifies the associated statistical profile toincorporate the defined one or more patient behavioral goals. In anotherembodiment, the behavioral calculator 2124 modifies a statisticalprofile to reflect the association between the defined behavioral goalsand the patient record stored in the patient record database 2116. Inyet another embodiment, the behavioral calculator 2124 stores thedefined behavioral goals in a separate database (not shown) and createsa logical association between the defined behavioral goals and thepatient record stored in the patient record database 2116.

Referring back to FIG. 6, the patient monitoring processor 2120 mayfurther determine that a patient statistical profile exists for apatient based on the received patient identification information (Block614). When the patient monitoring processor 2120 has finished processingthe patient statistical information for a pre-existing statisticalprofile, the patient monitoring processor 2120 may take a variety ofactions, depending on the clinician 2102 input. For example, the patientmonitoring system 2108 may prompt the clinician 2102 to select betweenmodifying the patient statistical profile (Block 618) or generating areport of the patient record (Block 620). Alternatively, the patientmonitoring processor 2120 could prompt the clinician 2102 to selectother actions, such as modifying the pre-existing statistical profilesfor one or more patients (Block 622), viewing one or more pre-existingstatistical profiles for one or more patients, (Block 624) editingpre-existing statistical profiles for one or more patients (Block 626),or combinations thereof. In yet another alternative embodiment, theclinician may be able to create another statistical profile (Block 616)for a patient that has a pre-existing statistical profile. In anotherembodiment, the variety of actions previously discussed (Blocks 618-626)may be performed if a patient profile does not exist for the patientassociated with the received patient identification information.

In providing a report of the patient record associated with apre-existing patient statistical profile, the provided report may bebased on a predetermined time frame, such as daily, weekly, monthly,yearly, or combinations thereof. The provided report could also be adynamic report based on a selected timeframe chosen by the clinician2102. In an alternative embodiment, the clinician 2102 may be able toaccess a compilation report of all patients that have similarcharacteristics, such as, similar objectives, goals, fault tolerances,statistical profiles, etc. FIG. 25 shows one example of a patient reportgenerated using the patient monitoring system 2108. FIG. 25 may beproduced based on the information in the patient record database 2116,the statistical profiles 2130, or a combination thereof. In oneembodiment of the patient monitoring system 2108, the clinician 2102,the patient 2104, the external data source 2106, or a combinationthereof, may add comments to the patient record stored in the patientrecord database 2116 for later reviewing in a patient report. FIG. 26shows an exemplary report having comments entered into a patient recordusing the patient monitoring system 2108. The clinician 1502 may alsogenerate monthly reports for individual patients. FIGS. 27-54 show otherexamples of individual monthly reports for patients involved in weightsurveys. By way of example, FIG. 27 shows that the maximum survey weightwas approximately 191 lbs., that the patient's weight fluctuated between186 lbs. and 190 lbs, inclusive, and that the minimum survey weight was184 lbs. Other individual reports are shown in FIGS. 28-54 and showsimilar graphical information, or no graphical information, depending onwhen the report was generated and the number of surveys the patientcompleted.

FIG. 9 illustrates a flowchart depicting the operation of modifying anexisting patient statistical profile according to one embodiment. Forexample, the clinician may provide additional information that affectsthe statistical profile associated with the patient record of thereceived patient identification information. As shown in FIG. 9, thestatistical processor 2122 receives the patient statistical informationfrom the patient monitoring processor 2120 (Block 902). The statisticalprocessor 2122 may receive the statistical information from the patientmonitoring processor 2122 over a wired link, a wireless link, or acombination thereof. In one embodiment, the patient monitoring processor2120 formats the statistical information in a format understandable bythe statistical processor 2122 as was described above.

After the statistical processor 2122 has received the patientstatistical information from the patient monitoring processor 2120, thestatistical processor 2122 then analyzes the received patientstatistical information (Block 904). For example, the statisticalprocessor 2122 may analyze the received patient statistical informationto determine whether the received patient statistical information is inthe correct format. The statistical processor 2122 may also analyze thereceived patient statistical information to determine whether thepatient statistical information is capable of modifying the patientstatistical profile, such as where the clinician provides informationregarding the successfulness of a particular treatment. Otherinformation affecting the statistical profile may include whether otherpatients have been successful in a particular line of treatments or,alternatively, if the particular treatments have had a high and/or lowfailure rate.

After the statistical processor 2122 analyzes the received patientstatistical information, the statistical processor 2122 then determineswhether to generate a new statistical profile (Block 906). If thestatistical processor 2122 determines that the provided patientstatistical information does not affect the previously existingstatistical profile, the statistical processor 2122 may proceed to afinishing state of modifying the statistical profile (Block 920). In oneembodiment, the statistical processor 2122 communicates with the patientmonitoring processor 2120 to inform the patient monitoring processor2120 that a new statistical profile is not needed.

Alternatively, the statistical processor 2122 may determine that a newstatistical profile is needed. If the statistical processor 2122 makesthis determination, the statistical processor 2122 generates a newstatistical profile (Block 908). In one example, the statisticalprocessor 2122 retains the information from the previously existingstatistical profile and supplements the information of the pre-existingstatistical profile with the received patient statistical information.In another example, the statistical processor 2122 generates a newstatistical profile from the received patient statistical information.In generating the new statistical profile, the statistical processor2122 may use the information from the pre-existing statistical profile,the received patient statistical information, or a combination thereof.The statistical processor 2122 may generate a patient statisticalprofile, a population statistical profile, or a combination thereof.

After generating a new statistical profile (Block 908), the statisticalprocessor 2122 then associates the generated statistical profile withthe patient record associated with the pre-existing statistical profile(Block 910). The statistical processor 2122 then communicates with thepatient behavioral calculator 2124 to recalculate the patient behavioralpath (Block 912) based on the generated statistical profile. Forexample, the patient behavioral calculator 2124 may calculate a newpatient behavioral path that accounts for the success or failure rate ofa particular treatment based on the new statistical profile.

Following the recalculation of the patient behavioral path, the patientbehavioral calculator 2124 then associates the new patient behavioralpath with the patient record (Block 914). After associating the patientbehavioral path with the patient record (Block 914), the patientbehavioral calculator 2124 proceeds to redefine the patient behavioralgoal(s) (Block 916). The redefining of the patient behavioral goals mayaccount for the recalculated patient behavioral path, the generated newstatistical profile, or combination thereof. The patient behavioralcalculator 2124 then associates the new patient behavioral goals withthe patient record (Block 918). The patient behavioral calculator 2124then informs the patient monitoring processor 2120 that the process ofmodifying a patient statistical profile is complete (Block 920) and,optionally, that it has finished calculating the behavioral path andredefining the behavioral goals.

Referring back to FIG. 1, after the clinician has finished accessing thepatient monitoring system (Block 118), the patient monitoring system2108 finishes the clinician session with the clinician (Block 122). Infinishing the clinician session, the patient monitoring processor 2120may review all of the accessing actions the clinician 2102 has takenduring the accessing session. The patient monitoring processor 2120could also provide an option for the clinician 2102 to review all of theprevious clinician sessions (if any), and the actions taken during thoseprevious clinician sessions. The patient monitoring processor 2120 couldalso verify the actions taken by the clinician 2102 during the cliniciansession and prompt whether the clinician 2102 wants to modify any (orall) of the actions taken during the clinician session. Once theclinician 2102 indicates that the clinician 2102 is satisfied withaccess session for the patient, the patient monitoring processor 2120terminates the session between the clinician 2102 and the patientmonitoring system 2108.

In addition to the access granted to a clinician 2102, a patient 2104,or a surrogate such as a clinician 2102 acting on behalf of a patient,as was described above, is also capable of accessing the patientmonitoring system 2108. In one embodiment, the patient 2104 communicateswith the patient monitoring system 2108 using an IVR interface. Inanother embodiment, the patient 2104 communicates with the patientmonitoring system 2108 using an interface designed for Internet access,such as a web page provided by a web site associated with the system2108. Other types of interfaces are also possible, such as an interfaceusing both audible and visual prompts. The patient 2104 proceeds tocommunicate with the patient monitoring system 2108 by initiating acommunication request (Block 102). The patient monitoring system 2108then prompts the patient 2104 to provide user identification information(Block 104).

In one embodiment, the patient user identification is a personalidentification number (PIN) associated with the patient record stored inthe patient record database 2116. In another embodiment, the patientuser identification is a combination of a username and password. Theuser identification information could further include biometricinformation associated with the patient record stored in the patientrecord database 2116. After the patient 2104 provides the useridentification information, the patient monitoring system 2108 receivesthe user identification information (Block 106). The patient monitoringsystem 2108 receives the user identification information overcommunication link 2132. The communication link 2132 could be apacket-switched network, a circuit-switched network, or a combinationthereof. The patient monitoring system 2108 then analyzes the useridentification information (Block 108).

Analyzing the user identification information provided by the patientmay include accessing the authorized users database 2134 by theinformation communication processor 2112. The information communicationprocessor 2112 could also access the patient record database 2116 todetermine whether the patient has authority to access the patientmonitoring system 2108 based on the provided user identificationinformation. In an alternative embodiment, the information communicationprocessor 2112 could access both the authorized users database 2134 andthe patient record database 2116 to determine whether the patient hasaccess to the patient monitoring system 2108. After the informationcommunication processor 2112 has analyzed the patient provided useridentification information (Block 108), the information communicationprocessor 2112 proceeds to the patient monitoring process (Block 120).When the patient 2104 completes the patient monitoring process (Block120), the patient monitoring system 2108 finishes the patient sessionwith the patient 2104 (Block 122).

FIG. 10 is a flowchart of one example of a patient accessing the patientmonitoring process (Block 120). The patient monitoring processor 2120first determines whether a patient record is available based on thepatient provided user identification information (1002). In oneembodiment, the patient monitoring processor 2120 communicates with thepatient enrollment processor 2114 to access the patient record database2116. The patient monitoring processor 2120 provides the useridentification information to the patient enrollment processor 2114 forretrieving a patient record from the patient record database 2116associated with the user identification information. In anotherembodiment, the patient monitoring processor 2120 accesses the patientrecord database 2116 to determine whether a patient record existsassociated with the patient provided identification information. If thepatient monitoring processor 2120 or a patient enrollment processor 2114determines that a patient record does not exist for the patient provideduser identification information, the patient monitoring processor 2120or the patient enrollment processor 2114 communicates with theinformation communication processor 2112 to prompt the patient toprovide further patient identification information (Block 1004). Forexample, the patient may have provided incorrect user identificationinformation and the patient monitoring system 2108 may have been unableto locate the patient record based on the incorrect patient provideduser identification information. After the information communicationprocessor 2112 has prompted the patient to provided further useridentification information, the patient monitoring system 2108 thenwaits for the patient to provide further user identificationinformation. In one embodiment, the patient monitoring system 2108disconnects the patient from the patient monitoring system 2108 after apredetermined amount of time measured in seconds, minutes, hours, othermeasurements of time, or combinations thereof. Once the patient hasprovided further user identification information, the patient monitoringsystem 2108 then receives the further user identification information(Block 1006). The patient monitoring processor 2120 then determineswhether a patient record exists in the patient record database 15 16based on the further provided user identification information.

If the patient monitoring processor 2120 determines that a patientrecord exists in the patient record database 2116 based on the patientprovided user identification information, the patient monitoringprocessor 2120 then retrieves the patient record from the patient recorddatabase 2116 (Block 1008). Alternatively, or in addition to theinformation provided from the patient record, the patient 2104 mayprovide patient statistical information to the patient monitoring 2120for selecting a targeted message to send to the patient 2104. Thepatient monitoring processor 2120 then selects a targeted message forthe patient (Block 1010). A targeted message is a message intended toelicit a response from the patient indicating whether the patient isproceeding along a behavioral path towards achieving a behavioralobjective. For example, the patient monitoring processor 2120 may selecta targeted message based on the patient questionnaire associated withthe patient record from the patient questionnaire database 2118. Thepatient monitoring processor 2120 may also select a targeted messagebased on the behavioral path associated with the patient record. Theselected targeted message could also be based on previous responses toprior targeted messages sent by the patient monitoring system 2108.

In one embodiment, the selected targeted message is a question from theassociated questionnaire, such as a message intended to elicit a directresponse, such as an affirmative answer or a negative response, from thepatient. For example, the desired behavioral objective by the patientmay be to wake up earlier in the morning. In this example, the targetedmessage is a question, such as “Did you wake up at 6:00 a.m.?” Inanother example, the desired behavioral objective by the patient may beto stop smoking. In this example, the targeted question is a differentquestion, such as “Did you smoke more than five cigarettes today?” Ineach example, the targeted message is designed to elicit a response fromthe patient. Other questions designed to elicit a response from thepatient are also possible.

In another embodiment, the selected targeted message is a messageintended to elicit an indirect response, such as a change in behavior bythe patient. For example, the patient may be required to communicatewith the patient monitoring system 2108 on a regular schedule to receivea particular positive or negative message. In this example, the targetedmessage is a statement, such as “Thank you for calling today, you aredoing a great job!” The targeted message could also be a negatorystatement, such as “You will not smoke today!”

When the patient monitoring processor 2120 has selected a targetedmessage, the patient monitoring processor then communicates the targetedmessage to the patient 2104 using the information communicationprocessor 2112 (Block 1012). In one embodiment, the targeted messagecommunicated to the patient 2104 is an audible message, such as wherethe patient 2104 communicates with the information communicationprocessor 2112 using an IVR interface. In another embodiment, thetargeted message communicated to the patient 2104 is a visual message,such as where the patient 2104 communicates with the informationcommunication processor 2112 using a computer. The targeted messagecould also be communicated to the patient 2104 using a combination ofaudible and visual prompts.

After communicating the targeted message to the patient 2104 (Block1012), the information communication processor 2112 then receives apatient response (Block 1014). In another embodiment, the informationcommunication processor 2112 analyzes the targeted message before it issent to determine whether a response is expected. For example, theinformation communication processor 2112 may expect to receive aresponse from the patient 2104 before sending the targeted message. Whenthe patient response is received by the information communicationprocessor 2112, the communication processor 2112 communicates thereceived response to the patient monitoring processor 2120. The patientmonitoring processor 2120 then determines whether a proper patientresponse was received (Block 1016). In one embodiment, the patientmonitoring processor 2120 has access to responses that are consideredproper based on the selected targeted message. For example, if theselected targeted message was “Did you smoke more than five cigarettestoday?”, the patient monitoring processor 2120 would expect a responsein the form of an affirmative or negative answer, such as “Yes” or “No.”However, in this example, if the patient 2104 provides an answer such as“Blue,” the patient monitoring processor 2120 would determine that thiswas not a proper response. The responses that are considered proper, orin a form considered proper, may be stored in a database coupled withthe patient monitoring system 2108. In another embodiment, the patientresponse is reviewed by an external actor, such as a clinician orhealthcare provider. If the patient monitoring processor 2120 determinesthat the response received from the patient is not a proper response,the patient monitoring processor 2120 prompts the patient for anotherresponse to the selected targeted message (Block 1018).

In another embodiment, the patient monitoring processor 2120 may presenta survey comprised of targeted messages as a web page based form thatthe patient 2104 fills out entirely and then submits, e.g. all of theresponses are submitted in batch to the patient monitoring system 2108.Alternatively, or in addition to the use of a web page, the patientmonitoring processor 2120 may present the survey of targeted messagesusing the IVR interface. In this embodiment, the patient monitoringprocessor 2120 analyzes the responses submitted by the patient 2104 atone time as a group rather than analyzing the responses individually.The patient monitoring processor 2120 may then proceed, as describedabove, in selecting additional targeted messages, surveys, orcombinations thereof, for answering by the patient 2104.

Once the patient monitoring processor 2120 has determined that a properpatient response has been received, the patient monitoring processor2120 then stores the patient's response (Block 1020). In one embodiment,the patient monitoring processor 2120 stores the patient responsedirectly in the patient record database 2116. For example, the patientmonitoring processor 2120 could create a logical association between thepatient record store in the patient record database 2116 and the patientresponse stored in the patient record database 2116. In anotherembodiment, the patient monitoring processor 2120 could store thepatient response in the patient record of the patient record database2116. For example, the patient monitoring processor 2120 could create anew field representing the patient's response in the patient recordstored in the patient record database 2116. In yet another embodiment,the patient monitoring processor 2120 could store the patient's responsein a separate database coupled with the patient monitoring processor2120 and logically associated with the patient record stored in thepatient record database 1560. The separate database could be part of thesame system as the patient monitoring processor 2120, part of adifferent system, or a combination thereof.

The patient monitoring processor 2120 then determines whether to selectanother targeted message for the patient (Block 1022). In oneembodiment, the patient monitoring processor 2120 makes thisdetermination based on whether there is a subsequent question remainingfrom the patient questionnaire associated with the patient record. Forexample, the patient monitoring processor 2120 may select a patientquestionnaire for the patient that has a series of questions, each ofwhich are to be answered sequentially. In another embodiment, thepatient monitoring processor 2120 selects another targeted message basedon the received patient response. For example, the patient monitoringprocessor 2120 could employ branching logic that determines a subsequenttargeted message to send based on the received patient response, such asdirected by the questionnaire. In yet another embodiment, the patientmonitoring processor 2120 could select another targeted message based onthe behavioral path associated with the patient record when comparedwith the received patient response. For example, the patient monitoringprocessor 2120 could determine that the patient is no longer on thebehavioral path based on the received patient response, and thereforeselect a targeted message designed to steer the patient back towards thepatient behavioral path. The patient monitoring processor 2120 may alsoutilize a combination of the patient questionnaire associated with thepatient record, the received patient response, and the patientbehavioral path and/or behavioral objective to select another targetedmessage. If the patient monitoring processor 2120 determines to selectanother targeted message (Block 1022), the patient monitoring processor2120 then selects the next targeted message (Block 1010).

If the patient monitoring processor 2120 determines not to selectanother targeted message, the patient monitoring processor 2120 thenends the patient monitoring session with the patient (Block 1024). Inone embodiment, the patient monitoring processor 2120 communicates withthe patient 2104 to inform the patient 2104 that the patient monitoringsession has ended. For example, the patient monitoring processor 2120 orthe information communication processor 2112 could send audible and/orvisual prompt to the patient 2104 informing the patient 2104 of the endof the session, depending on the type of interface used. Where thepatient 2104 communicates with the patient monitoring processor 2120using an IVR interface, the patient monitoring processor 2120 or theinformation communication processor 2112 may send an audible prompt tothe patient 2104 alerting the patient 2104 to the end of the patientmonitoring session. Alternatively, where the patient 2104 communicateswith the patient monitoring processor 2120 using an Internet interface,such as a web page, the patient monitoring processor 2120 or theinformation communication processor 2112 could send an audible/visualprompt to the patient 2104 allowing the patient 2104 to the end of thepatient monitoring session. Other types of communication are alsopossible.

After the patient monitoring system 2108 has ended the patientmonitoring session with the patient 2104 (Block 1024), the patientmonitoring processor 2120 then formats and sends the one or more patientresponses to the patient goal analyzer 2126 (Block 1026). For example,the patient goal analyzer 2126 may expect the patient response to be ina format different than the format received by the patient monitoringprocessor 2120. Such formats include, but are not limited to,text-files, binary files, comma-delimited files, proprietary formats,other types of files, or combinations thereof. Where the patient goalanalyzer 2126 expects the one or more patient responses in a formatdifferent than one or more patient responses received by the patientmonitoring processor 2120, the patient monitoring processor 2120performs format conversion on the received one or more patientresponses.

The patient goal analyzer 2126 is configured to analyze the receivedpatient responses. In one embodiment, the patient goal analyzer 2126 isa programmable processor that analyzes the patient responses todetermine whether the patient is meeting the patient behavioral goals.

FIG. 11 depicts a flowchart of analyzing a patient's response to atargeted message. In one embodiment, the patient goal analyzer 2126receives the one or more patient responses from the patient monitoringprocessor 2120 (Block 1102). When the patient goal analyzer 2126 hasreceived the one or more patient responses from the patient monitoringprocessor 2120, the patient goal analyzer 2126 then retrieves the storedpatient behavioral goals (Block 1104). Alternatively, the patient goalanalyzer 2126 could have retrieved the stored patient behavioral goalsbefore receiving the one or more patient responses from the patientmonitoring processor 2120. In one embodiment, the patient goal analyzer2126 retrieves the stored patient behavioral goals from the patientrecord stored in the patient record database 2126. In anotherembodiment, the patient goal analyzer 2126 retrieves the stored patientbehavioral goals from the statistical profile associated with thepatient record stored in the patient record database 2116. In yetanother embodiment, the patient goal analyzer 2126 retrieves the storedpatient behavioral goals from a patient behavioral goal database. Othertypes of retrieval are also possible.

After the patient goal analyzer 2126 has received both the one or morepatient responses from the patient monitoring processor 2120 and thestored patient behavioral goals, the patient goal analyzer 2126 thenperforms an analysis on the one or more patient responses using thepatient behavioral goals (Block 1106). In one embodiment, the patientgoal analyzer 2126 compares the received one or more patient responseswith the current behavioral goal. For example, the behavioral objectivescould be for the patient to stop smoking entirely. To achieve thatobjective, there may be multiple intermediates behavioral goals, and thecurrent behavioral goal may be to stop smoking four packs of cigarettesa day. The patient goal analyzer 2126 would been compared to receivedone or more patient responses with the current goal, being stop smokingfour packs of cigarettes a day, and then produce a goal analysisindicating whether the patient is meeting the current behavioral goal.In another example, the behavioral objective could be for the patient towake up at six o'clock in the morning. To achieve that objective, theremay be multiple intermediates behavioral goals, and the current goal inmaybe to wake of acts that clock in the morning. The patient goalanalyzer 2126 within compare the received one or more patient responseswith the current goal, being to wake up at nine o'clock in the morningand then produce a goal and office indicating whether the patient ismeeting that current behavioral goal.

In another embodiment, the patient goal analyzer 2126 compares thereceived one or more patient responses with the set of intermediategoals along the behavioral path. For example, the behavioral objectivemay be for the patients to stop smoking entirely and there may bemultiple intermediates behavioral goals along the behavioral path, suchas to stop smoking five packs of cigarettes a day, then to stop smokingthree packs of cigarettes a day, then to stop smoking one pack ofcigarettes a day, and so forth. In this example, the patient goalanalyzer 2126 would compare the received one or more responses with theset of intermediate goals to determine whether the patient is on aforward path in meeting those goals. If the received one or more patientresponses indicate that the patient has smoked six packs of cigarettesfor the day, the patient goal analyzer 2126 would indicate that thepatient is no longer on a forward path to meeting the intermediatebehavioral goals. In contrast, if the received one or more patientresponses indicate that the patient has smoked to this packs ofcigarettes for the day, the patient goal analyzer 2126 would indicatethat the patient is on a forward path to meeting the intermediatebehavioral goals.

In yet another embodiment, the patient goal analyzer 2126 compares thereceived one or more patient responses with the behavioral pathassociated with the patient. For example, the behavioral path mayindicate a particular threshold which is considered acceptable to thepatient monitoring system 2108. If the received one or more patientresponses indicate that the patient is no longer on a net positiveprogress along the behavioral path the patient goal analyzer 2126 wouldindicate the failure in the net positive progress.

In yet a further embodiment, the patient goal analyzer 2126 compares thereceived one or more patient responses with the previously stored one ormore patient responses with the stored patient behavioral goals. Forexample, the patient goal analyzer 2126 may account for the history ofall the received one or more patient responses, including, or excluding,the current received one or more patient responses, and based on thishistory could determine whether the patient has been making progresstowards achieving a behavioral goal and/or the behavioral objective. Thepatient goal analyzer 2126 could also assign priorities to differentpatient behavioral goals and indicates based on those priorities whetherthe patient is making progress towards achieving the patient behavioralobjective.

After the patient goal analyzer 2126 has analyzed the one and morepatient responses, the patient goal analyzer 2126 then communicates withthe patient monitoring processor 2120 to determine whether to initiatethe failure prevention mechanism 2128 of the patient monitoring system2108 (Block 1108). The decision to initiate the failure preventionmechanism (Block 1108) may occur concurrently or subsequent to thepatient goal analyzer 2126 sending an analysis of the received one ormore patient responses to the statistical processor 2122 (Block 1112).If the patient goal analyzer 2126 determines that the received one ormore patient responses indicates that the failure prevention mechanismshould be initiated, the patient goal analyzer 2126 communicates withthe patient monitoring processor 2120 to initiate the failure preventionmechanism (Block 1110) (See FIG. 13). In one embodiment, the decision toinitiate the failure prevention mechanism is based on whether thepatient has achieved the current behavioral goal. For example, if thecurrent behavioral goal is to stop smoking four packs of cigarettes aday and the received one or more patient responses indicates that thepatient has in fact smoked five packs of cigarettes for the day, thepatient goal analyzer 2126 would then inform the patient monitoringprocessor 2120 to initiate the failure prevention mechanism 2128.

In another embodiment, the decision to initiate the failure preventionmechanism 2128 is based on the number of times the patient has failed tomeet the current behavioral goal. For example, the patient goal analyzer2126 may determine that the number of times a patient can fail a currentbehavioral goal is four times. If the received one or more patientresponses indicates that the patients has failed to meet the currentbehavioral goal more than four times, the patient goal analyzer 2126would then inform the patient monitoring processor 2120 to initiate thefailure prevention mechanism 2128.

In yet another embodiment, the decision to initiate the failureprevention mechanism 2128 is based on whether that the patient has madenet progress towards achieving the patient behavioral objective alongthe behavioral path. For example, if the received one or more patientresponses indicate that the patient has not made progress or has madenegative progress along the patient behavioral path, the patient goalanalyzer 2126 would inform the patient monitoring processor 2120 toinitiate the failure prevention mechanism 2128. Where the decision toinitiate the failure prevention mechanism is based on a patient makingnet progress along the patient behavioral path, the patient goalanalyzer 2126 could also account for the time elapsed between the lasttime the patient had net positive progress and the patient's currentprogress. Other factors the patient goal analyzer 2126 could considerinclude net failure, the different priorities assigned to the behavioralgoals, the amount of time the patient has been on the behavioral pathtowards achieving the behavioral objective, or other combinations offactors.

When the patient goal analyzer 2126 has finished analyzing the receivedone or more patient responses, the patient goal analyzer 2126 sends theanalysis to the statistical processor 2122. FIG. 12 is a flowchartdepicting the operations of modifying a statistical profile of thedisclosed patient monitoring system according to one embodiment. Asshown in FIG. 12, the statistical processor 2122 receives the patientgoal analysis from the patient goal analyzer 2126 (Block 1202). Thestatistical processor 2122 then analyzes the received patient goalanalyses (Block 1204). In one embodiment, the statistical processor 2122analyzes the patient goal analysis to determine whether a selectedtargeted message elicited a response that indicated progress towards abehavioral goal. For example, if the selected targeted message was “Didyou smoke four packs of cigarettes today?”, and the goal analysisindicated that the patient had not achieved a particular goal based onthis selected targeted message, the statistical processor 2122 wouldnote that the selected targeted message did not help the patient achievea particular goal. In another example, if the selected targeted messagewas “You need to stop smoking or you will die!”, and the patient goalanalysis indicated that the patient had achieved a particular goal basedon the selected targeted message, the statistical processor 2122 wouldindicate that this selected targeted message was helpful for the patientin the achieving a particular goal. In another embodiment, thestatistical processor 2122 analyzes the patient goal analysis and thepatient record stored in the patient records database 2116. For example,the statistical processor 2122 may analyze the patient's demographicinformation and compare that with the patient goal analysis to determinewhether a selected targeted message or a particular method of treatmentis helping that patient meet his/her behavioral goals for that patientin that demographic. In one example, the statistical processor 2122 mayanalyze the patient's age, and based on that patient's age inconjunction with the received patient goal analysis the statisticalprocessor 2122 may determine whether a selected targeted message ishelping a patient of that age achieve a patient behavioral goal. Otherdemographic, health history and physical exam information may includethe patient's nationality, the patient's birthplace, the patient height,diabetes status, the patient's weight, and other such information. Inyet a further embodiment, the statistical processor 2122 analyzes healthrelated information of the patient, such as prior medical history,nutritional diet, and physical fitness, with the patient goal analysisto determine whether a selected targeted message or a particulartreatment is beneficial in helping the patient achieve the patient'sbehavioral goal and/or the patient's behavioral objective.

After analyzing the received patient goal analysis (Block 1204), thestatistical processor 2122 then determines whether to adjust/modify thestatistical profile associated with the patient (Block 1206). In oneembodiment, the statistical processor 2122 modifies the statisticalprofile associated with the patient where the analysis indicates thatthe patient is meeting a particular behavioral goal. For example, thestatistical processor 2122 may modify the statistical profile toindicate that a selected targeted message helps a patient achieve apatient behavioral goal. In another example, the statistical processor2122 modifies the statistical profile to indicate that a selectedtargeted message does not help a patient achieve the patient behavioralgoal. In another embodiment, the statistical processor 2122 adjusts thestatistical profile to include further information that may not havebeen previously present when the statistical profile was initiallycreated. For example, the statistical processor 2122 may add furtherinformation that was not previously accounted for. In one embodiment thestatistical processor may add new information reflecting changes toparticular data over time acquired through analysis of the patientrecord database entries for similar patients or for the current patient.For example, through the use of statistical process controls, thestatistical processor may update associated population statisticalprofiles and/or patient statistical profiles associated with one or morepatients based on responses to targeted messages, surveys, additionalinput from the clinician 2102, patient 2104, or external data source2106, through information requested by the patient monitoring system2108, or combinations thereof.

In another embodiment the statistical processor may have updated thestatistical profiles related to the current patient. Statisticalprocessor 2122 could also remove information that the statisticalprocessor 2122 determines is superfluous or detrimental for the patient.The statistical processor 2122 could determine that the statisticalprofile associated with the patient should only contain information thathelps a patient achieve a patient goal. Alternatively, the statisticalprocessor 2122 may also determine that the statistical profile shouldcontain information about both the failures and successes for thepatient in achieving a patient behavioral goal.

The statistical profile could also reflect the treatments and/or theselected targeted message that are beneficial in achieving a patientbehavioral objective. The modifications to the statistical profile mayalso reflect the treatment analysis or the selected targeted messagethat are detrimental in achieving a patient behavioral objective.Furthermore, the statistical processor 2122 may also modify thestatistical profile based on demographic or condition for a particulargroup of patients. For example, if the patient monitoring system 2108 ismonitoring several patients, the statistical processor 2122 maydetermine that a particular exercise is more beneficial than acomparative exercise based on response received for those particularpatients. The statistical processor 2122 may then incorporate thisknowledge into future questions or questionnaires to prompt othermonitored or future patients.

In adjusting/modifying the statistical profile associated with thepatient, the statistical processor 2122 may generate a new statisticalprofile for the patient based on the analysis of the patient goalanalysis (Block 1208). Generating a new statistical profile may includeretaining the old statistical profile, supplementing the old statisticalprofile, removing the old statistical profile, or a combination thereof.After generating a new statistical profile (Block 1208), the statisticalprocessor 2122 associates the generated statistical profile with thepatient record of the received patient goal and analysis (Block 1210).The statistical processor 2122 then communicates with the patientbehavioral calculator 2124 to recalculate the patient behavioral path(Block 1212). Alternatively, the patient behavioral calculator 2124 maydetermine not to recalculate the patient behavioral path based on thegenerated statistical profile. The patient behavioral calculator 2124then proceeds to associate the patient behavioral path with the patientrecord (Block 1214) and to redefine the patient behavioral goals (Block1216). The patient behavioral calculator 2124 then associates thepatient behavioral goals with the patient record for the receivedpatient goal analysis (Block 1218).

After determining whether to adjust/modify the statistical profileassociated with the received patient goal analysis (Block 1206), thestatistical processor 2122 then determines whether to modify theselected targeted message(s) or select one or more different messagessent to the patient (Block 1220). In an alternative embodiment, theclinician 2102 could instruct the statistical processor 2122 to modifythe selected target message(s), or to select one or more differentmessages. In one embodiment, the statistical processor 2122 analyzes thetargeted message(s) sent to the patient based on the received patientgoal analysis and modifies a selected targeted message (Block 1222), ifnecessary. For example, if the selected targeted message sent to thepatient was “Keep up the great job!”, and the analysis of the patientgoal analysis indicated that this selected targeted message did not helpthe patient achieve the patient behavioral goal and/or the patientbehavioral objective, the statistical processor 2122 may modify theselected targeted message from “Keep up the great job!” to “I am verydisappointed in you.”

In another embodiment, the statistical processor 2122 also modifies thetype and/or tone of the selected targeted message sent to the patient.For example, if the selected targeted message sent to the patient was“Did you smoke four packs of cigarettes today?”, and the analysis of thepatient goal analysis indicated that this selected targeted message didnot help the patient achieve a patient behavioral goal analysis or thepatient behavioral objective, the statistical processor 2122 may modifythe selected targeted message from “Did you smoke four packs ofcigarettes today?” to “You need to stop smoking four packs ofcigarettes!”

In yet another embodiment, the statistical processor 2122 modifiesfuture targeted messages for the patient. For example, if thestatistical processor 2122 determines that a type of targeted message,such as a positive reinforcement targeted message, is not helping thepatient to achieve a patient behavioral goal and/or a patient behavioralobjective, the statistical processor 2122 may change future targetedmessages to negative reinforcement targeted messages. Other types ofmodifications to future targeted messages include modifying the quantitymentioned in the targeted message, modifying the subject of the targetedmessage, or of the targeted message.

In yet a further embodiment, the statistical processor 2122 modifies thetargeted messages where the statistical processor 2122 decides toadjust/modify the statistical profile associated with the patientrecord. For example, a newly generated statistical profile based onadjustments and/or modifications by the statistical processor 2122 mayrequire a new set, or a different set, of targeted messages for thepatient. Once the statistical processor 2122 has finished modifying thetargeted messages 1222, the statistical processor 2122 then finishesprocessing the patient goal analysis (Block 1224). For example, thestatistical processor 2122 may inform the patient monitoring processorthat it has finished processing the patient goal analysis.

Referring to FIG. 13 is a flowchart for activating a failure preventionmechanism 2128 of the patient monitoring system 2108. The failureprevention mechanism 2128 of the patient monitoring system 2108 is amechanism designed to prevent a patient from failing to achieve abehavioral objective and/or a particular behavioral goal along thebehavioral path to the behavioral objective. In one embodiment, thefailure prevention mechanism 2128 is a human alert system (See FIG.23A). In another embodiment, the failure prevention mechanism 2128 is afailure prevention database (See FIG. 23B). According to the embodimentshown in FIG. 13, the patient monitoring processor 2120 receivesnotification to initiate the failure prevention mechanism 2128 (Block1302). For example, the patient monitoring processor 2120 may receive anotification to initiate the failure prevention mechanism 2128 from thepatient goal analyzer 2126. After receiving a notification to initiatethe failure prevention mechanism 2128 (Block 1302), the patientmonitoring processor 2128 then selects a failure prevention mechanism2128 (Block 1304).

In one embodiment, the patient monitoring processor 2120 selects boththe human alert system and the failure prevention database. In anotherembodiment, the patient monitoring processor 2120 selects the failureprevention mechanism 2128 based on predefined criteria. The predefinedcriteria includes factors such as the number of times the patient hasfailed to meet a behavioral goal, the total number of times the patienthas failed to meet a behavioral goal, the severity of failing to meet abehavioral goal, whether the patients is no longer on the behavioralpath, or a combination thereof. Other factors may also account for thedemographic of the patient, the patient's history in achieving abehavioral objective, whether the patient record indicates a patientpreference for a particular failure prevention mechanism 2128, orwhether the patient requires human intervention.

The clinician 2102, in establishing the patient record, may alsoindicate whether the patient monitoring processor 2120 selects the humanalert system or the failure prevention database as the failureprevention mechanism 2128. Once the patient monitoring processor 2120has selected a failure prevention mechanism 2128, the patient monitoringprocessor 2120 then activates that failure prevention mechanism 2128. Ifthe patient monitoring processor 2120 decides that human intervention isrequired, the patient monitoring processor 2120 then activates the humanalert system as the failure prevention mechanism 2128 (Block 1306) (Seeabove with reference to FIG. 23A). If the patient monitoring processor2120 decides to send a failure prevention message, the patientmonitoring processor 2120 then activates the failure prevention databaseas the failure prevention mechanism 2128 (Block 1308) (See above withreference to FIG. 23B).

After the patient monitoring processor 2120 has activated the failureprevention database (Block 1308), the patient monitoring processor 2120then chooses a failure prevention message from the failure preventiondatabase (Block 1310). In an alternative embodiment, a separate failureprevention processor communicates with the patient monitoring processor2120 to choose a failure prevention message from the failure preventiondatabase. In one embodiment, choosing a failure prevention message fromthe failure prevention database is based on the severity of the patientin failing to achieve a particular behavioral goal and/or a behavioralobjective. For example, if the patient goal analyzer 2126 communicatesto the patient monitoring processor 2120 that the patient failed toachieve a particularly significant behavioral goal, the patientmonitoring processor 2120 would then select a failure prevention messagethat communicates this severity, such as “You missed a really importantgoal and you need to continue in working towards that goal.” In anotherembodiment, choosing a failure prevention message from the failureprevention database is based on the number of times a patient has failedto achieve a particular goal and/or a behavioral objective. For example,the failure prevention messages stored in the failure preventiondatabase may be rated in severity and the rating may correspond to thenumber of times at patient has failed to meet a goal. In yet anotherembodiment, choosing a failure prevention message from the failureprevention database is sequentially based such that each failureprevention message is guaranteed to be sent at least once to the patientdepending on the number of failures by the patient.

Before the failure prevention is sent, the patient monitoring processor2120, or other failure prevention processor, determines whether tomodify the failure prevention message (Block 1312). In one embodiment,the failure prevention messages are purposely generic but are tailoredto the unique demographics of the patient before sending. In anotherembodiment, the failure prevention messages are modified to correspondto the severity of the failure by the patient in failing to achieve abehavioral goal and/or behavioral objective. The modifications to thefailure prevention message could also be based on a temporal basis, suchas adding or removing words that reflect the day, week, or month onwhich the failure prevention message was sent. Modifications to thefailure prevention message may include, but are not limited to,additions, deletions, edits, insertions, or other modifying actions. Thefailure prevention message could also be modified to reflect personalinformation of the patient, such as the patient's name, home address,prior medical history, other personal information, or combinationthereof. Once the patient monitoring processor 2120 has determined tomodify a failure prevention message, the failure prevention message isthen modified (Block 1314).

After a determination has been made as to whether to modify a failureprevention message (Block 1312), the patient monitoring system 2108sends the failure prevention message (Block 1316). In one embodiment,the failure prevention message is an audible message sent to the patient2104 over communication link 2132. For example, where the patient 2104communicates with the patient monitoring system 2108 using an IVRinterface, the failure prevention message would be sends as an audiblemessage to the patient 2104. In another embodiment, the failureprevention message is an audible and/or visual message sent to thepatient 2104 over communication link 2132 such as where the patient 2104communicates with the patient monitoring system 2108 using an interfacedesigned for the Internet, such as a web page of a web site. In yetanother embodiment, the failure prevention message is sent to thepatient after the patient has finished the patient monitoring sessionwith the patient monitoring system 2108. The failure prevention messagecould also be sent while the patient is communicating with the patientmonitoring system 2108. The patient 2104 may also have the option ofselecting when to receive the failure prevention message.

FIG. 14 is a flowchart of one embodiment of evaluating patient inputusing a statistical processor. The information communication processor2112 communicates the survey to the patient 2104 according to thepatient statistical profile 2130 (Block 1402) and receives the patientresponse to the survey (Block 1404). The survey communicated to thepatient 2104 may contain one or more patient questionnaires associatedwith the patient record of the patient 2104. After receiving the patientresponse to the survey (Block 1404), the statistical processor 2122receives a request from the patient monitoring processor 2120 toinitiate a longitudinal cohort analysis (Block 1406). The statisticalprocessor 2122 queries the patient monitoring processor 2120 todetermine whether this is the first survey data for the patient 2104using the current patient statistical profile 2130 (Block 1408). If thisis the first survey, the statistical processor 2122 requests data fromthe patient record database 2116 (Block 1410) and from the patientstatistical profile 2130 (Block 1412). The statistical processor usesinput from patient record database 2116, the patient statistical profile2130, or a combination thereof, to perform a cross-sectional baselineanalysis (Block 1414), as explained below with reference to FIG. 15. Inan alternative embodiment, a baseline analysis is performed (Block 1414)after any subsequent survey. After a baseline analysis has beenperformed (Block 1414), a longitudinal cohort analysis is then performed(Block 1416), as explained below with reference to FIG. 16. In analternative embodiment, the longitudinal cohort analysis is performed ifthe survey communicated to the patient is not the first survey. Aftercompleting the longitudinal cohort analysis (Block 1416), survey resultsare assimilated into the patient record database 2116 (Block 1418).

In one embodiment, the patient monitoring processor 2120 directs theinformation communication processor 2112 to communicate a survey to thepatient 2104 and receive the patient responses (Block 1404). The patientmonitoring processor 2120 may then store the results in the patientrecord database 2116. The patient monitoring processor 2120 thenrequests the statistical processor 2122 to initiate the longitudinalcohort analysis (Block 1406). In an alternative embodiment, theclinician 2102, the patient 2104, the external data source 2106, or acombination thereof, instructs the statistical processor 2122 toinitiate the longitudinal cohort analysis (Block 1406).

In one embodiment, the appropriate cohort set includes all subjects whoshare one or more characteristics that are related to either possiblepatient behavioral interventions or to desirable outcomes. In analternative embodiment, the appropriate cohort set includes only asubset of patients who share one or more characteristics that arerelated to either possible patient behavioral interventions or todesirable outcomes. The appropriate cohort set is then stored in thestatistical profile of the patient. In one embodiment the appropriatecohort may be identified by the system automatically based on theoutcome of interest, treatment options, and the associated statisticalprofile. In another embodiment the appropriate cohort may be entered bythe clinician 2102 directly, received from an external data source 2106,assigned a default value by the system 2108, or a combination thereof.

If the current survey is the first survey for the current patient, thestatistical processor 2122 requests patient data from the patientmonitoring processor 2120 for both the current patient and theappropriate cohort of patients, which abstracts the appropriate datafrom the patient record database 2116, reformats the data if necessaryand forwards it to the statistical processor 2122. The statisticalprocessor 2122 then performs a cross-sectional baseline analysis (Block114) to determine whether the patient statistical profile should bechanged, whether the appropriate cohort set should be changed andwhether the patient behavioral goals should be recalculated.

FIG. 15 is a flowchart depicting operation of the statistical processor2122 performing a cross-sectional baseline analysis according to oneembodiment. In one embodiment, the input from the patient recorddatabase 2116 is analyzed (Block 1502) to automatically determine theappropriate cohort or sub-population for the current patient based onpredictors of clinical and behavioral outcomes associated with theoutcomes (Block 1506). In an alternate embodiment, these predictors arecontained in the statistical profile 2130 for the current patient. In afurther embodiment, these predictors are stored in the patent recorddatabase 2116. For example, if the desired outcome is related to acombination of lipid value goals, the characteristics identifying thecohort would include sex, diabetic status and statin usage as well asother predictors. A statistical profile of the cohort is then generated(Block 1506). This profile contains descriptions of the distributions ofmedical and behavioral outcome measures, including but not limited to,mean, standard deviation and percentiles of those distributions afterappropriate transformations for continuous measures and percentages bycategory for categorical outcomes.

Input from the individual patient record is analyzed (Block 1508) and isprofiled against the cohort profile (Block 1510). In one embodiment, theprofile is limited to those predictors that are available for thecurrent patient. In another embodiment, an imputation method, such as amodel-based imputation, hot deck imputation, imputation to the mean ormedian or multiple imputations, are used to impute values that aremissing in the current patient record.

Profiling may involve one or more medical or behavioral outcomemeasures, which in turn may be either continuous or categorical.Profiling, in one embodiment, may treat each outcome individually whileanother may treat them as a single multivariate outcome. For example,diabetes status may treated alone, but systolic and diastolic bloodpressure may be treated as a single two-dimensional outcome. Continuousoutcomes might be profiled using predictive modeling, including but notlimited to methods such as generalized linear models, generalized mixedeffects models, generalized estimating equations, time series models,tree-structured regression, Bayesian models, nearest neighbor methods,clustering or scaling algorithms or neural networks. Categorical modelsmight be profiled using some of the same methods mentioned forcontinuous outcomes where appropriate, but might also include othertechniques, including but not limited to discriminate analysis, Bayesianclassifiers and tree-structured classifiers.

Individual baseline outcomes are then calculated (Block 1512). In oneembodiment, these are calculated based on the predictive relationshipsdetermined when generating the statistical profile of the cohort (Block1506). In another embodiment, these are calculated based on statisticalprofiles of patients derived from relevant literature. A thirdembodiment uses predictive relationships on advice solicited from anexpert panel. Another embodiment combines the two or more approachesdepending upon the nature of the outcomes and the strength of theevidence in the literature, expert panel or patient record database.Hence, the contribution of the patient record database grows with thenumber of subjects captured in it. Techniques for determining combiningproportions may include, but are not limited to, fixed proportions,proportions based upon an information measure, any now known or laterdeveloped technique, or combination thereof. In one embodiment, thebaseline outcome is a single number or category for each outcomemeasure. In another embodiment, the outcomes are probabilitydistributions for each outcome measure, whether continuous, categorical,multivariate, or combination thereof.

Individual predicted intervention outcomes are then calculated (Block1514). These are similar to the baseline outcomes, except that theimpact of the intervention is factored into the calculation. Theseoutcomes may be calculated individually for each medical and behavioraloutcome or may be calculated jointly, as a single multivariate outcome.In one, embodiment this involves fitting new models as in calculatingthe individual baseline outcome (Block 1512), but restricting the cohortto subjects who complied with the planned intervention. In anotherembodiment, this involves including predictors that track with theactive intervention. For subjects in the cohort that are missinginformation on interventions or compliance, models might includeimputation, multiple imputation, or combinations thereof. As withindividual baseline outcomes, predicted intervention outcomes may be asingle number or may be probability distributions, indicating thelikelihood of a variety of outcomes.

After calculating the predicted intervention outcome (Block 1514), thepredicted difference between the baseline predicted outcome and theintervention predicted outcome is calculated (Block 1516). Thisdifference may be calculated as a difference in value for a numericalmeasure, a difference in category, as a probability distribution for adifference in numerical or categorical outcome, or a combinationthereof. In one embodiment, the difference is a single number derivedfrom the difference of the individual baseline outcome and the predictedintervention outcome. In another embodiment, the difference is modeleddirectly. For example, a mixed effect model may be used to estimate thedifference in rate of change over time resulting from an intervention.In another embodiment, a Bayesian predictive model is used to estimatethe probability distribution of values over time based on the presenceor absence of an intervention. In yet another embodiment, a Markov modelis used to predict probabilities of a variety of possible outcomeclasses as a function of time and other predictors.

Baseline and predicted intervention fault tolerances are then calculated(Block 1518). In one embodiment, fault tolerances are derived frompredictive models using model-based estimates of variability. In anotherembodiment, bootstrap analyses is used to estimate variability ofestimates based on the cohort. In another embodiment, jackknife or splitsample techniques (such as using a training and test sample approach)are used to estimate variability. Another embodiment uses a combinationof some or all of the above approaches.

The baseline outcome, intervention outcome and fault tolerance limitsare then stored in the individual patient record (Block 1520). Thestatistical processor communicates the requested results to the patientmonitoring processor 2120, which then stores the information in thepatient record database 2116.

FIG. 16 is a flowchart depicting operation of the statistical processor2122 performing a longitudinal cohort analysis according to oneembodiment. The longitudinal cohort analysis begins by assessing theinterval outcome of the patient based on the survey data (Block 1602).The fault tolerance limits are retrieved from the patient record (Block1604), and these are compared with the interval outcome (Block 1606).The comparison of the interval outcome with the fault tolerancedetermines whether the fault limit has been crossed (Block 1608). If afault limit has been crossed, then an intervention is triggered (Block1612), and the interval outcome is stored in the patient record database2116 (Block 1610). If a fault limit is not crossed, the interval outcomeis stored in the patient record database 2116 (Block 1614), and anassessment occurs to determine whether the predicted interventionoutcome has been reached (Block 1616). If the outcome has been reached,the patient survey process is completed (Block 1618). For example, ifthe predicted intervention outcome is to stop a patient from smoking andthe statistical processor 2122, or other processor, determines that thepatient has reached this predicted intervention outcome based on thepatient's responses to the one or more surveys presented, thestatistical processor 2122, or other processor, discontinues presentingsurveys to the patient.

If the predicted intervention outcome has not been reached, such aswhere the statistical processor 2122 determines that the patient iscontinuing to smoke, the interval outcome is assessed to determine ifone of the statistical thresholds has been met (Block 1620). Forexample, if the statistical threshold is that the patient is to reducesmoking down to five cigarettes a day, and the statistical processor2122, or other processor, determines that the patient has reducedsmoking down to 3 cigarettes day, the statistical processor 2122, orother processor, will determine that the statistical threshold has beenmet. As another example, a statistical threshold may be that the patientis to reach the predicted intervention outcome of not smoking withinfour sessions with the patient monitoring system 2108. If a thresholdhas been met, such as where the statistical processor 2122, or otherprocessor, has determined that the patient is at his or her fifthsession, a cross-section analysis based on the current interval outcomeis calculated (Block 1622), and the statistical threshold is reset(Block 1624). The next survey may then be selected irrespective ofwhether the statistical threshold was met (Block 1626). In this fashion,a patient may proceed towards the predicted intervention outcome untilthe statistical processor 2122, or other processor, determines that thepatient has met the predicted intervention outcome.

The comparison of the interval outcome with fault tolerance limits(Block 1606) may occur in a variety of ways. In one embodiment, thecomparison is a simple comparison of a final value to a higher and lowerboundary. In another embodiment, the comparison of the interval outcomewith the fault tolerance limits stored in the patient record database2116 follow process control guidelines, where various rules related toobservations falling a certain distance above or below the mean resultin a triggering event. In another embodiment, fault tolerance limits arerelated to stopping boundaries, such as O'Brien-Fleming boundaries orPocock-boundaries, as those are used in clinical trials based uponspending functions. In another embodiment, the comparison is Bayesianmodel-based, with updated posterior distributions crossing adistributional tolerance limit.

The comparison of the interval outcome to the intervention outcome(Block 1616) may occur similar to the comparison with tolerance limits(Block 1606). Alternatively, the comparison may involve the comparisonof the most recent value in the interval with a value indicatingsuccess. The comparison of the interval outcome with the statisticalthreshold (Block 1620) may also occur similar to the comparison with thefault tolerance limits (Block 1606).

If a statistical threshold is met without reaching the interventionoutcome, the behavioral goal is adjusted (Block 1622). FIG. 17 is aflowchart depicting operation of the statistical processor 2122performing a cross-sectional analysis using calculated interval outcomesto adjust the behavioral objective according to one embodiment. Thestatistical processor 2122 first receives the calculated intervaloutcomes (Block 1702) and input from the patient record database 2116relating to the interval outcomes (Block 1704). It is possible that theinformation stored in the patient record database 2116 will have changedsince the previous cross-section baseline analysis. The statisticalprocessor 2122 then uses the information from the patient recorddatabase 2116 and the calculated interval outcomes to calculate newfault limit values (Block 1606). In one embodiment, new fault limits arecalculated using Bayesian averaging of a variability estimate from thepatient record database 2116 together with an estimate derived from theinterval outcome. In another embodiment, the new fault limits are basedon a variability estimate derived from the interval outcome alone. Thenew fault limits are then in either the patient record database 2116,the patient statistical profiles 2130, or a combination thereof.

Referring back to FIG. 14, the assimilation of survey results into thepatient record database 2116 (Block 1418) may occur in a variety of waysdepending upon the type of survey data. For example, if data is receivedfrom an external data source 2106, such as a remote blood sugar monitor,this information may be stored directly in the patient record database2116. If data is received from a an external data source 2106,derivative measures may also be calculated and stored. For example, aremote blood pressure monitor may report systolic and diastolic bloodpressure, with pulse pressure calculated from these two and stored alongwith them. Alternatively, if data is received in the form of responsesto a questionnaire, the raw responses, normalized responses, transformedresponses, or scales and subscales, or combinations thereof may bestored in the patient record database 2116. The choice of assimilationmethod will vary from one embodiment to another and depend upon the typeof data collected.

FIG. 18 is a graphical illustration of one embodiment of the patientstatistical profiles 1930 showing the time 1812 of a patient in movingfrom a baseline set of cohorts 1804 to a another set of cohorts 1806associated with a predicted intervention outcome profile 1810. Asexplained above with reference to FIG. 15, when an enrolled patientanswers the first survey, the statistical processor 2122 determines thebaseline cohort set 1804 and profiles the patient provided responses tothe first survey against the baseline cohort set 1804 to determine abaseline patient statistical profile 1808. Alternatively, or in additionto the answers provided by the patient 2104 in answering the firstsurvey, the statistical processor 2122 may use previously providedinformation, such as from information stored in the patient recorddatabase 2116, to determine a baseline cohort set 1804 and a baselinepatient statistical profile 1808. In another embodiment, the statisticalprocessor 2122 may use statistical information provided by the clinician2102, the patient 2104, or an external data source 2106, or combinationsthereof, to determine the baseline cohort set 1804 and the baselinestatistical profile 1808.

The statistical processor 2122 then calculates the predictedintervention outcome profile 1810. The statistical processor 2122 thencalculates the difference between the baseline patient statisticalprofile 1808 and the predicted intervention outcome profile 1810. Basedon the difference between the baseline patient statistical profile 1808and the predicted intervention outcome profile 1810, the statisticalprocessor 2122 is able to calculate a patient behavioral path to helpthe patient 2104 achieve the predicted intervention outcome profile 1810and the set of patients 1806 associated with the predicted interventionoutcome profile 1810.

FIG. 19 is a diagram of one embodiment of a patient behavioral path1902. As described above with reference to FIG. 15, when the patient2104 completes a first survey, the statistical processor 2122 calculatesa baseline outcome 1906 based on the patient responses to that firstsurvey. The statistical processor 2122 then calculates a patientbehavioral path 1902 and a predicted intervention outcome 1912. Usingthe population cohort set, the statistical processor 2122 thencalculates fault tolerance limits 1904 between the baseline outcome 1906and the predicted intervention outcome 1912. As the patient 2104completes each survey, the statistical processor 2122 calculates aninterval outcome 1908 and compares the interval outcome 1908 with thefault tolerance limits 1904. Where the statistical processor 2122calculates an interval outcome 1910 outside the fault tolerance limits1904, the statistical processor 2122 triggers the failure preventionmechanism 2128. As the patient 2104 completes surveys, the statisticalprocessor 2122 may re-calculate the fault tolerance limits 1904 based onthe responses provided by the patient to those surveys. As shown in theembodiment of FIG. 19, the fault tolerance limits 1904 decrease as thestatistical processor 2122 calculates each subsequent interval outcome1908. Alternatively, the fault tolerance limits 1904 may also increase,or otherwise vary, as the patient 2104 answers each survey. Thealterations in the fault tolerance limits 1904 encourage the patient2104 to proceed along the patient behavioral path 1902 until the patientreaches the predicted intervention outcome 1912.

FIG. 20 is a flowchart depicting the operation of contacting a patientwhen the patient fails to contact the patient monitoring system,according to one embodiment. In one embodiment, a patient associatedwith the patient monitoring system 2108 has a schedule that the patientis expected to adhere to while the patient is being monitored. Forexample, the patient may be expected to contact the patient monitoringsystem 2108 on a weekly basis. Each time the patient contacts thepatient monitoring system 2108, the patient monitoring system 2108resets the patient session schedule (Block 2002). The patient maycontact the patient monitoring system 2108 according to schedule, aheadof the schedule, behind schedule, or combinations thereof. Where thepatient contacts the patient monitoring system 2108 ahead of schedule,the patient monitoring system 2108 adjusts the patient contact scheduleaccordingly, such as by moving each subsequent scheduled contact periodahead proportionally.

As an example, suppose that the patient schedule starts on a Monday suchthat the patient monitoring system 2108 expects the patient to contactthe patient monitoring system 2108 every Monday. After the patientmonitoring system 2108 has reset the patient session schedule (Block2002), the patient monitoring system 2108 then waits for the patient toinitialize a patient session (Block 2004). In this example, the patientmonitoring system 2108 checks whether it is to expect the patient tocontact it. If the patient monitoring system 2108 expects the patient tocontact it, the patient monitoring system 2108 then determines whetherthe patient has, in fact, initialized the patient session (Block 2006).If the patient initialized the patient session with the patientmonitoring system 2108, the patient monitoring system 2108 then resetsthe patient schedule (Block 2002).

However, if the patient did not initialize a patient session, thepatient monitoring system 2108 then decrements a patient session timer(Block 2008). In one embodiment, the patient session timer is a timerthat extends to the patient a grace period before the patient monitoringsystem contacts the patient. In the example where the patient isexpected to contact the patient monitoring system 2108 every Monday, thepatient session timer may allow the patient a four-day grace periodbefore contacting the patient. For example, if the patient was expectedto contact the patient monitoring system 2108 on a Monday, but failed tocontact the patient monitoring system 2108 and the day is now Tuesday,the patient monitoring system 2108 will decrement the patient sessiontimer by one day. The patient session timer may be measured in othertime increments such as seconds, minutes, and hours, weeks, months, oreven years. Other temporal measurements are also possible.

The patient monitoring system 2108 then determines whether the patientsession timer has expired (Block 2010). If the patient session timer hasnot expired, the system then proceeds to expect as patient sessioninitialization (Block 2004). In the example where the patient isexpected to contact the patient monitoring system 2108 every Monday, thepatient monitoring system 2108 may wait one day before determiningwhether the patient initialize a patient session (Block 2006). Thepatient monitoring system 2108 continues in this manner until thepatient monitoring system 2108 determines that the patient session timerhas expired. If the patient monitoring system 2108 determines that thepatient session timer has expired (Block 2010), the patient monitoringsystem 2108 then attempt to initiate a patient session with the patient(Block 2012). In the example where the patient is expected to contactthe patient monitoring system 2108 every Monday, and there is a missedcontact, the patient monitoring system 2108 will attempt to initiatecontact with the patient, such as by telephone, the Internet, a mobilecommunication device, by mail, or other communication medium or device,or combination thereof.

Once the patient monitoring system has attempted to initiate a patientsession with the patient (Block 2010), the patient monitoring system2108 then determines whether it was successful in establishing a patientsession (Block 2014). If the patient monitoring system 2108 wassuccessful in establishing a patient session, the patient monitoringsystem 2108 then resets the patient session schedule (Block 2002). Inthe example of where the patient is expected to contact the patientmonitoring system 2108 every Monday, if the patient monitoring system2108 establishes the patient session with the patient, the patientmonitoring system 2108 will reset the patient schedule such as to expecta patient session the following Monday. If the patient monitoring system2108 was unsuccessful in establishing a patient session, the patientmonitoring system 2108 may continue subsequent attempts to contact thepatient. For example, the patient monitoring system 2108 may bepreprogrammed to continue contacting a patient once every 24 hours. Inanother example, the patient record may reflect how often the patientmonitoring system 2108 should continue contacting the patient after thepatient monitors system 2108 was unsuccessful in establishing a patientsession. The patient monitoring system 2108 continues contacting thepatient until the patient monitoring system 2108 reaches a contactinglimits that has been predefined by the system, by the patient, by theclinician, or combination thereof. When the patient monitoring system2108 reaches the contacting limit, the patient monitoring system 2108then determines whether it should continue contacting the patient (Block2016).

If the patient monitoring system 2108 determines that it should notcontinue contacting the patient, the patient monitoring system requestsclinician intervention (Block 2022). For example, the patient monitoringsystem 2108 may contact a clinician of associated with the patientrecord over a communication medium such as telephone, the Internet, awireless communication device, postal mail, or combination thereof. Inanother embodiment, the patient monitoring system 2108 is preprogrammedto contact a specific clinician when the patient monitoring system 2108determines that should not continue contacting the patient. In anotherembodiment, the patient monitoring system 2108 requests intervention byan entity other than the clinician, such as a health-care provider, orpatient caregiver. After the patient monitoring system 2108 hasrequested clinician intervention (Block 2022), the patient monitoringsystem 2108 then finishes its attempts to initiate the patient sessionwith the patient (Block 2024). In one embodiment, the patient monitoringsystem 2108 records the number of times it had attempted to contact thepatient. In another embodiment, the patient monitoring system 2108modifies the patient record to reflect that the patient may no longer beactive in the patient monitoring system 2108.

If the patient monitoring system 2108 decides it should continuecontacting the patient, the patient monitoring system 2108 records afailure to establish a patient session in the patient's record stored inthe patient record database 2116 (Block 2018). The recorded failure mayindicate the number of times the patient monitoring system 2108attempted to contact the patient, the days on which the patientmonitoring system 2108 attempted to contact the patient, the conditionsunder which the patient monitoring system 2108 attempted to contact thepatient, or other related information. After recording the failure toestablish the patient session, the patient monitoring system 2108 thenreconfigures the patient initialization schedule such as to expected thepatient to initialize a session more frequently (Block 2020). In anotherembodiment, the patient monitoring system 2108 reconfigures the patientinitialization schedule such as to expect the patient to contact thepatient monitoring system 2108 less frequently. In a further embodiment,the patient monitoring system 2108 reconfigures the patientinitialization schedule based on a predefined schedule associated withthe patient's record stored in the patient record database 2116. Othersources of information for reconfiguring the patient initializationschedule may include the clinician, the patient, a health-care provider,patient monitoring devices, or combination thereof. Alternatively, or inaddition to, reconfiguring the patient initialization schedule, thepatient monitoring system 2108 initializes a failure preventionmechanism 2128 to contact the patient 2104. Once the patient monitoringsystem 2108 has established contact with the patient after it hasreconfigured the patient initialization schedule (Block 2020), thepatient monitoring system 2108 then resets the patient session scheduleto the initial schedule that was created for the patient (Block 2002).

While various embodiments of the invention have been described, it willbe apparent to those of ordinary skill in the art that many moreembodiments and implementations are possible within the scope of theinvention. Accordingly, the invention is not to be restricted except inlight of the attached claims and their equivalents.

We claim:
 1. A method for directing behavior of a first patient of aplurality of patients towards a behavioral objective, the methodcomprising: calculating, with a processor, a first behavioral path tothe behavioral objective for the first patient based on an initial stateof the first patient and a first statistical profile of the firstpatient, the first statistical profile being operative, for an inputbased on the first patient, to produce a most likely output of a modeledpatient-population, based on a comparison of the input of the firstpatient with the modeled patient-population; selecting a type oftargeted message, wherein the type of targeted message includes apositive reinforcement targeted message or a negative reinforcementtargeted message; generating a first targeted message based on thecalculated first behavioral path and the selected type of targetedmessage; sending the first targeted message during a first session tomotivate the first patient to achieve the behavioral objective andelicit a first response representative of a result thereof; modifyingthe first statistical profile based on the first response; recalculatingthe first behavioral path to the behavioral objective for the firstpatient based on the modified first statistical profile of the firstpatient; re-selecting the selected type of targeted message based on thefirst response; and generating a second targeted message based on therecalculated first behavioral path and the re-selected type of targetedmessage.
 2. The method of claim 1, further comprising establishing afirst session with the first patient, wherein sending the first targetedmessage comprises sending the first targeted message to the firstpatient during the first session.
 3. The method of claim 1, wherein thefirst statistical profile of the patient comprises a statistical profileof the plurality of patients, a patient specific statistical profile, ora combination thereof.
 4. The method of claim 1, further comprisingdefining a first plurality of intermediate behavioral goals along thecalculated first behavioral path for achieving the behavioral objective.5. The method of claim 1, further comprising: establishing a secondsession with the first patient; sending the second targeted message tothe first patient during the second session to motivate the firstpatient to achieve the behavioral objective and elicit a second responsefrom the first patient representative of a result thereof; andmodifying, based on the second response, the modified first statisticalprofile.
 6. The method of claim 1, further comprising: calculating asecond behavioral path to the behavioral objective for a second patientof the plurality of patients based on an initial state of the secondpatient and a second statistical profile of the second patient, whereinthe second statistical profile of the second patient is based on thefirst statistical profile of the first patient; determining a secondtargeted message based on the second behavioral path; establishing asecond session with the second patient; sending the second targetedmessage to the second patient during the second session to motivate thesecond patient to achieve the behavioral objective of the secondbehavioral path and elicit a second response from the second patientrepresentative of a result thereof; and modifying, based on the secondresponse, the second statistical profile.
 7. The method of claim 1,further comprising calculating the first statistical profile of thefirst patient based on provided statistical information.
 8. The methodof claim 1, further comprising determining whether the firstintermediate behavioral goal has been achieved based on the firstresponse.
 9. The method of claim 9, further comprising intervening whenthe first patient fails to achieve the first intermediate behavioralgoal.
 10. A method for directing behavior of a first patient of aplurality of patients towards a behavioral objective, the methodcomprising: calculating a first behavioral path for a first patient of aplurality of patients based on an initial state of the first patient anda first statistical profile of the first patient, wherein the firstbehavioral path comprises a first individual baseline outcome and afirst predicted intervention outcome.
 11. The method of claim 10,wherein the first statistical profile of the patient comprises astatistical profile of the plurality of patients, a patient specificstatistical profile, or combination thereof.
 12. The method of claim 10,further comprising: calculating a first baseline fault tolerance limitbased on a magnitude of difference between the first individual baselineoutcome and the first predicted intervention outcome; determining afirst survey for communicating to the first patient based on thecalculated first behavioral path; sending the first survey to the firstpatient to motivate the first patient to achieve the first predictedintervention outcome and to elicit a first response from the firstpatient indicative of a result thereof; and calculating a first intervaloutcome based on the elicited first response.
 13. The method of claim12, further comprising: determining a second survey for communicating tothe first patient based on the calculated first behavioral path and thecalculated first interval outcome; sending the second survey to thefirst patient to motivate the first patient to achieve the firstpredicted intervention outcome and to elicit a second response from thefirst patient indicative of a result thereof; and calculating a secondinterval outcome based on the elicited second response.
 14. The methodof claim 13, further comprising: calculating a second fault tolerancelimit based on comparing the first interval outcome and the secondinterval outcome with the first baseline fault tolerance limit;determining a third survey for communicating to the first patient basedon the calculated first behavioral path and the calculated second faulttolerance limit; sending the third survey to the first patient tomotivate the first patient to achieve the first predicted interventionoutcome and to elicit a third response from the first patient indicativeof a result thereof; and calculating a third interval outcome based onthe elicited third response.
 15. The method of claim 14, furthercomprising: comparing the first interval outcome with the calculatedfirst baseline fault tolerance limit; and intervening when the firstinterval outcome exceeds the calculated first baseline fault tolerancelimit.
 16. The method of claim 12, further comprising: modifying thefirst statistical profile of the first patient based on the firstinterval outcome of the first patient; calculating a second behavioralpath for a second patient of the plurality of patients based on aninitial state of the second patient and a second statistical profile ofthe second patient, wherein the second statistical profile of the secondpatient is based on the first statistical profile of the first patient,and the second behavioral path comprises a second individual baselineoutcome and a second predicted intervention outcome; calculating asecond baseline fault tolerance limit based on a magnitude of differencebetween the second individual baseline outcome and the second predictedintervention outcome; determining a second survey for communicating tothe second patient based on the calculated second behavioral path;sending the second survey to the second patient to motivate the secondpatient to achieve the second predicted intervention outcome and toelicit a second response from the second patient indicative of a resultthereof; and, calculating a second interval outcome based on theelicited second response.
 17. The method of claim 16, furthercomprising: comparing the second interval outcome with the calculatedsecond baseline fault tolerance limit; calculating a third faulttolerance limit based on the comparison of the second interval outcomewith the calculated second baseline fault tolerance limit; determining athird survey for communicating to the second patient based on thecalculated second behavioral path and the calculated third faulttolerance limit; sending the third survey to the second patient tomotivate the second patient to achieve the second predicted interventionoutcome and to elicit a third response from the second patientindicative of a result thereof; and calculating a third interval outcomebased on the elicited third response.
 18. A method for directingbehavior of a first patient of a plurality of patients towards abehavioral objective, the method comprising: calculating a firstbehavioral path to the behavioral objective for the first patient basedon an initial state of the patient and a first statistical profile ofthe patient; selecting a type of targeted message, wherein the type oftargeted message includes a positive reinforcement targeted message or anegative reinforcement targeted message; generating a first targetedmessage based on the calculated first behavioral path and the selectedtype of targeted message; sending the first targeted message to motivatethe first patient to achieve the behavioral objective; receiving a firstresponse representative of a result of the sending; modifying the firststatistical profile of the first patient based on the first response;recalculating the first behavioral path to the behavioral objective forthe first patient based on the modified first statistical profile of thefirst patient; re-selecting the selected type of targeted message basedon the first response; and generating a second targeted message based onthe recalculated first behavioral path and the re-selected type oftargeted message.
 19. The method of claim 18, wherein the firststatistical profile is operative, for an input of the first patient, toproduce a most likely output from among a modeled patient-population,based on a comparison of the input of the first patient with the modeledpatient-population.
 20. The method of claim 19, wherein the sendingcomprises sending the first targeted message during the first session tomotivate the first patient to achieve the behavioral objective andelicit a first response representative of a result thereof